spaCy/spacy/pipeline/entity_linker.py

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import random
from itertools import islice
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Optional, Union
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
import srsly
from thinc.api import Config, CosineDistance, Model, Optimizer, set_dropout_rate
from thinc.types import Floats2d
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
from .. import util
from ..errors import Errors
from ..kb import Candidate, KnowledgeBase
from ..language import Language
from ..ml import empty_kb
from ..scorer import Scorer
from ..tokens import Doc, Span
from ..training import Example, validate_examples, validate_get_examples
from ..util import SimpleFrozenList, registry
from ..vocab import Vocab
from .legacy.entity_linker import EntityLinker_v1
from .pipe import deserialize_config
from .trainable_pipe import TrainablePipe
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
# See #9050
BACKWARD_OVERWRITE = True
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
default_model_config = """
[model]
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
@architectures = "spacy.EntityLinker.v2"
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
[model.tok2vec]
@architectures = "spacy.HashEmbedCNN.v2"
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
pretrained_vectors = null
width = 96
depth = 2
embed_size = 2000
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
window_size = 1
maxout_pieces = 3
subword_features = true
"""
DEFAULT_NEL_MODEL = Config().from_str(default_model_config)["model"]
@Language.factory(
"entity_linker",
requires=["doc.ents", "doc.sents", "token.ent_iob", "token.ent_type"],
assigns=["token.ent_kb_id"],
default_config={
"model": DEFAULT_NEL_MODEL,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
"labels_discard": [],
"n_sents": 0,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
"incl_prior": True,
"incl_context": True,
"entity_vector_length": 64,
2020-09-03 18:31:14 +03:00
"get_candidates": {"@misc": "spacy.CandidateGenerator.v1"},
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
"get_candidates_batch": {"@misc": "spacy.CandidateBatchGenerator.v1"},
"generate_empty_kb": {"@misc": "spacy.EmptyKB.v2"},
"overwrite": True,
"scorer": {"@scorers": "spacy.entity_linker_scorer.v1"},
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
"use_gold_ents": True,
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
"candidates_batch_size": 1,
"threshold": None,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
},
2020-09-24 18:10:35 +03:00
default_score_weights={
"nel_micro_f": 1.0,
"nel_micro_r": None,
"nel_micro_p": None,
},
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
)
def make_entity_linker(
nlp: Language,
name: str,
model: Model,
*,
labels_discard: Iterable[str],
n_sents: int,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
incl_prior: bool,
incl_context: bool,
entity_vector_length: int,
get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates_batch: Callable[
[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
],
generate_empty_kb: Callable[[Vocab, int], KnowledgeBase],
overwrite: bool,
scorer: Optional[Callable],
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
use_gold_ents: bool,
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates_batch_size: int,
threshold: Optional[float] = None,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
):
"""Construct an EntityLinker component.
model (Model[List[Doc], Floats2d]): A model that learns document vector
representations. Given a batch of Doc objects, it should return a single
array, with one row per item in the batch.
labels_discard (Iterable[str]): NER labels that will automatically get a "NIL" prediction.
n_sents (int): The number of neighbouring sentences to take into account.
incl_prior (bool): Whether or not to include prior probabilities from the KB in the model.
incl_context (bool): Whether or not to include the local context in the model.
entity_vector_length (int): Size of encoding vectors in the KB.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
produces a list of candidates, given a certain knowledge base and a textual mention.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates_batch (
Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]], Iterable[Candidate]]
): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
generate_empty_kb (Callable[[Vocab, int], KnowledgeBase]): Callable returning empty KnowledgeBase.
scorer (Optional[Callable]): The scoring method.
use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
component must provide entity annotations.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates_batch_size (int): Size of batches for entity candidate generation.
threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the threshold,
prediction is discarded. If None, predictions are not filtered by any threshold.
"""
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
if not model.attrs.get("include_span_maker", False):
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
# The only difference in arguments here is that use_gold_ents and threshold aren't available.
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
return EntityLinker_v1(
nlp.vocab,
model,
name,
labels_discard=labels_discard,
n_sents=n_sents,
incl_prior=incl_prior,
incl_context=incl_context,
entity_vector_length=entity_vector_length,
get_candidates=get_candidates,
overwrite=overwrite,
scorer=scorer,
)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
return EntityLinker(
nlp.vocab,
model,
name,
labels_discard=labels_discard,
n_sents=n_sents,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
incl_prior=incl_prior,
incl_context=incl_context,
entity_vector_length=entity_vector_length,
get_candidates=get_candidates,
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates_batch=get_candidates_batch,
generate_empty_kb=generate_empty_kb,
overwrite=overwrite,
scorer=scorer,
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
use_gold_ents=use_gold_ents,
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates_batch_size=candidates_batch_size,
threshold=threshold,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
)
def entity_linker_score(examples, **kwargs):
return Scorer.score_links(examples, negative_labels=[EntityLinker.NIL], **kwargs)
@registry.scorers("spacy.entity_linker_scorer.v1")
def make_entity_linker_scorer():
return entity_linker_score
class EntityLinker(TrainablePipe):
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
"""Pipeline component for named entity linking.
DOCS: https://spacy.io/api/entitylinker
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
"""
NIL = "NIL" # string used to refer to a non-existing link
def __init__(
self,
vocab: Vocab,
model: Model,
name: str = "entity_linker",
*,
labels_discard: Iterable[str],
n_sents: int,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
incl_prior: bool,
incl_context: bool,
entity_vector_length: int,
get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates_batch: Callable[
[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
],
generate_empty_kb: Callable[[Vocab, int], KnowledgeBase],
overwrite: bool = BACKWARD_OVERWRITE,
scorer: Optional[Callable] = entity_linker_score,
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
use_gold_ents: bool,
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates_batch_size: int,
threshold: Optional[float] = None,
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
) -> None:
"""Initialize an entity linker.
vocab (Vocab): The shared vocabulary.
model (thinc.api.Model): The Thinc Model powering the pipeline component.
name (str): The component instance name, used to add entries to the
losses during training.
labels_discard (Iterable[str]): NER labels that will automatically get a "NIL" prediction.
n_sents (int): The number of neighbouring sentences to take into account.
incl_prior (bool): Whether or not to include prior probabilities from the KB in the model.
incl_context (bool): Whether or not to include the local context in the model.
entity_vector_length (int): Size of encoding vectors in the KB.
get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
produces a list of candidates, given a certain knowledge base and a textual mention.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
get_candidates_batch (
Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]],
Iterable[Candidate]]
): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
generate_empty_kb (Callable[[Vocab, int], KnowledgeBase]): Callable returning empty KnowledgeBase.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links.
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
component must provide entity annotations.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates_batch_size (int): Size of batches for entity candidate generation.
threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the
threshold, prediction is discarded. If None, predictions are not filtered by any threshold.
DOCS: https://spacy.io/api/entitylinker#init
"""
if threshold is not None and not (0 <= threshold <= 1):
raise ValueError(
Errors.E1043.format(
range_start=0,
range_end=1,
value=threshold,
)
)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
self.vocab = vocab
self.model = model
self.name = name
self.labels_discard = list(labels_discard)
# how many neighbour sentences to take into account
self.n_sents = n_sents
self.incl_prior = incl_prior
self.incl_context = incl_context
self.get_candidates = get_candidates
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
self.get_candidates_batch = get_candidates_batch
self.cfg: Dict[str, Any] = {"overwrite": overwrite}
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
self.distance = CosineDistance(normalize=False)
self.kb = generate_empty_kb(self.vocab, entity_vector_length)
self.scorer = scorer
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
self.use_gold_ents = use_gold_ents
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
self.candidates_batch_size = candidates_batch_size
self.threshold = threshold
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
if candidates_batch_size < 1:
raise ValueError(Errors.E1044)
2020-10-08 11:34:01 +03:00
def set_kb(self, kb_loader: Callable[[Vocab], KnowledgeBase]):
"""Define the KB of this pipe by providing a function that will
create it using this object's vocab."""
if not callable(kb_loader):
raise ValueError(Errors.E885.format(arg_type=type(kb_loader)))
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
self.kb = kb_loader(self.vocab) # type: ignore
2020-10-08 11:34:01 +03:00
def validate_kb(self) -> None:
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
# Raise an error if the knowledge base is not initialized.
if self.kb is None:
raise ValueError(Errors.E1018.format(name=self.name))
if hasattr(self.kb, "is_empty") and self.kb.is_empty():
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
raise ValueError(Errors.E139.format(name=self.name))
2020-09-28 22:35:09 +03:00
def initialize(
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
self,
get_examples: Callable[[], Iterable[Example]],
*,
2020-09-29 13:20:26 +03:00
nlp: Optional[Language] = None,
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167) * 🚨 Ignore all existing Mypy errors * 🏗 Add Mypy check to CI * Add types-mock and types-requests as dev requirements * Add additional type ignore directives * Add types packages to dev-only list in reqs test * Add types-dataclasses for python 3.6 * Add ignore to pretrain * 🏷 Improve type annotation on `run_command` helper The `run_command` helper previously declared that it returned an `Optional[subprocess.CompletedProcess]`, but it isn't actually possible for the function to return `None`. These changes modify the type annotation of the `run_command` helper and remove all now-unnecessary `# type: ignore` directives. * 🔧 Allow variable type redefinition in limited contexts These changes modify how Mypy is configured to allow variables to have their type automatically redefined under certain conditions. The Mypy documentation contains the following example: ```python def process(items: List[str]) -> None: # 'items' has type List[str] items = [item.split() for item in items] # 'items' now has type List[List[str]] ... ``` This configuration change is especially helpful in reducing the number of `# type: ignore` directives needed to handle the common pattern of: * Accepting a filepath as a string * Overwriting the variable using `filepath = ensure_path(filepath)` These changes enable redefinition and remove all `# type: ignore` directives rendered redundant by this change. * 🏷 Add type annotation to converters mapping * 🚨 Fix Mypy error in convert CLI argument verification * 🏷 Improve type annotation on `resolve_dot_names` helper * 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors` * 🏷 Add type annotations for more `Vocab` attributes * 🏷 Add loose type annotation for gold data compilation * 🏷 Improve `_format_labels` type annotation * 🏷 Fix `get_lang_class` type annotation * 🏷 Loosen return type of `Language.evaluate` * 🏷 Don't accept `Scorer` in `handle_scores_per_type` * 🏷 Add `string_to_list` overloads * 🏷 Fix non-Optional command-line options * 🙈 Ignore redefinition of `wandb_logger` in `loggers.py` * ➕ Install `typing_extensions` in Python 3.8+ The `typing_extensions` package states that it should be used when "writing code that must be compatible with multiple Python versions". Since SpaCy needs to support multiple Python versions, it should be used when newer `typing` module members are required. One example of this is `Literal`, which is available starting with Python 3.8. Previously SpaCy tried to import `Literal` from `typing`, falling back to `typing_extensions` if the import failed. However, Mypy doesn't seem to be able to understand what `Literal` means when the initial import means. Therefore, these changes modify how `compat` imports `Literal` by always importing it from `typing_extensions`. These changes also modify how `typing_extensions` is installed, so that it is a requirement for all Python versions, including those greater than or equal to 3.8. * 🏷 Improve type annotation for `Language.pipe` These changes add a missing overload variant to the type signature of `Language.pipe`. Additionally, the type signature is enhanced to allow type checkers to differentiate between the two overload variants based on the `as_tuple` parameter. Fixes #8772 * ➖ Don't install `typing-extensions` in Python 3.8+ After more detailed analysis of how to implement Python version-specific type annotations using SpaCy, it has been determined that by branching on a comparison against `sys.version_info` can be statically analyzed by Mypy well enough to enable us to conditionally use `typing_extensions.Literal`. This means that we no longer need to install `typing_extensions` for Python versions greater than or equal to 3.8! 🎉 These changes revert previous changes installing `typing-extensions` regardless of Python version and modify how we import the `Literal` type to ensure that Mypy treats it properly. * resolve mypy errors for Strict pydantic types * refactor code to avoid missing return statement * fix types of convert CLI command * avoid list-set confustion in debug_data * fix typo and formatting * small fixes to avoid type ignores * fix types in profile CLI command and make it more efficient * type fixes in projects CLI * put one ignore back * type fixes for render * fix render types - the sequel * fix BaseDefault in language definitions * fix type of noun_chunks iterator - yields tuple instead of span * fix types in language-specific modules * 🏷 Expand accepted inputs of `get_string_id` `get_string_id` accepts either a string (in which case it returns its ID) or an ID (in which case it immediately returns the ID). These changes extend the type annotation of `get_string_id` to indicate that it can accept either strings or IDs. * 🏷 Handle override types in `combine_score_weights` The `combine_score_weights` function allows users to pass an `overrides` mapping to override data extracted from the `weights` argument. Since it allows `Optional` dictionary values, the return value may also include `Optional` dictionary values. These changes update the type annotations for `combine_score_weights` to reflect this fact. * 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer` * 🏷 Fix redefinition of `wandb_logger` These changes fix the redefinition of `wandb_logger` by giving a separate name to each `WandbLogger` version. For backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` as `wandb_logger` for now. * more fixes for typing in language * type fixes in model definitions * 🏷 Annotate `_RandomWords.probs` as `NDArray` * 🏷 Annotate `tok2vec` layers to help Mypy * 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6 Also remove an import that I forgot to move to the top of the module 😅 * more fixes for matchers and other pipeline components * quick fix for entity linker * fixing types for spancat, textcat, etc * bugfix for tok2vec * type annotations for scorer * add runtime_checkable for Protocol * type and import fixes in tests * mypy fixes for training utilities * few fixes in util * fix import * 🐵 Remove unused `# type: ignore` directives * 🏷 Annotate `Language._components` * 🏷 Annotate `spacy.pipeline.Pipe` * add doc as property to span.pyi * small fixes and cleanup * explicit type annotations instead of via comment Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 16:21:40 +03:00
kb_loader: Optional[Callable[[Vocab], KnowledgeBase]] = None,
2020-09-29 13:20:26 +03:00
):
"""Initialize the pipe for training, using a representative set
of data examples.
get_examples (Callable[[], Iterable[Example]]): Function that
returns a representative sample of gold-standard Example objects.
2020-09-29 13:20:26 +03:00
nlp (Language): The current nlp object the component is part of.
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates a KnowledgeBase from a Vocab
instance. Note that providing this argument will overwrite all data accumulated in the current KB.
Use this only when loading a KB as-such from file.
DOCS: https://spacy.io/api/entitylinker#initialize
"""
validate_get_examples(get_examples, "EntityLinker.initialize")
if kb_loader is not None:
2020-10-08 11:34:01 +03:00
self.set_kb(kb_loader)
self.validate_kb()
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
nO = self.kb.entity_vector_length
doc_sample = []
vector_sample = []
for eg in islice(get_examples(), 10):
doc = eg.x
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
if self.use_gold_ents:
ents, _ = eg.get_aligned_ents_and_ner()
doc.ents = ents
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
doc_sample.append(doc)
vector_sample.append(self.model.ops.alloc1f(nO))
assert len(doc_sample) > 0, Errors.E923.format(name=self.name)
assert len(vector_sample) > 0, Errors.E923.format(name=self.name)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
# XXX In order for size estimation to work, there has to be at least
# one entity. It's not used for training so it doesn't have to be real,
# so we add a fake one if none are present.
# We can't use Doc.has_annotation here because it can be True for docs
# that have been through an NER component but got no entities.
has_annotations = any([doc.ents for doc in doc_sample])
if not has_annotations:
doc = doc_sample[0]
ent = doc[0:1]
ent.label_ = "XXX"
doc.ents = (ent,)
self.model.initialize(
X=doc_sample, Y=self.model.ops.asarray(vector_sample, dtype="float32")
)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
if not has_annotations:
# Clean up dummy annotation
doc.ents = []
def batch_has_learnable_example(self, examples):
"""Check if a batch contains a learnable example.
If one isn't present, then the update step needs to be skipped.
"""
for eg in examples:
for ent in eg.predicted.ents:
candidates = list(self.get_candidates(self.kb, ent))
if candidates:
return True
return False
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
def update(
self,
examples: Iterable[Example],
*,
drop: float = 0.0,
sgd: Optional[Optimizer] = None,
losses: Optional[Dict[str, float]] = None,
) -> Dict[str, float]:
"""Learn from a batch of documents and gold-standard information,
Revert "Set annotations in update" (#6810) * Revert "Set annotations in update (#6767)" This reverts commit e680efc7cc365a31c1c7f9d5eb8733c1e61e558d. * Fix version * Update spacy/pipeline/entity_linker.py * Update spacy/pipeline/entity_linker.py * Update spacy/pipeline/tagger.pyx * Update spacy/pipeline/tok2vec.py * Update spacy/pipeline/tok2vec.py * Update spacy/pipeline/transition_parser.pyx * Update spacy/pipeline/transition_parser.pyx * Update website/docs/api/multilabel_textcategorizer.md * Update website/docs/api/tok2vec.md * Update website/docs/usage/layers-architectures.md * Update website/docs/usage/layers-architectures.md * Update website/docs/api/transformer.md * Update website/docs/api/textcategorizer.md * Update website/docs/api/tagger.md * Update spacy/pipeline/entity_linker.py * Update website/docs/api/sentencerecognizer.md * Update website/docs/api/pipe.md * Update website/docs/api/morphologizer.md * Update website/docs/api/entityrecognizer.md * Update spacy/pipeline/entity_linker.py * Update spacy/pipeline/multitask.pyx * Update spacy/pipeline/tagger.pyx * Update spacy/pipeline/tagger.pyx * Update spacy/pipeline/textcat.py * Update spacy/pipeline/textcat.py * Update spacy/pipeline/textcat.py * Update spacy/pipeline/tok2vec.py * Update spacy/pipeline/trainable_pipe.pyx * Update spacy/pipeline/trainable_pipe.pyx * Update spacy/pipeline/transition_parser.pyx * Update spacy/pipeline/transition_parser.pyx * Update website/docs/api/entitylinker.md * Update website/docs/api/dependencyparser.md * Update spacy/pipeline/trainable_pipe.pyx
2021-01-25 17:18:45 +03:00
updating the pipe's model. Delegates to predict and get_loss.
examples (Iterable[Example]): A batch of Example objects.
drop (float): The dropout rate.
sgd (thinc.api.Optimizer): The optimizer.
losses (Dict[str, float]): Optional record of the loss during training.
Updated using the component name as the key.
RETURNS (Dict[str, float]): The updated losses dictionary.
DOCS: https://spacy.io/api/entitylinker#update
"""
self.validate_kb()
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
if losses is None:
losses = {}
losses.setdefault(self.name, 0.0)
if not examples:
return losses
validate_examples(examples, "EntityLinker.update")
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
set_dropout_rate(self.model, drop)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
docs = [eg.predicted for eg in examples]
# save to restore later
old_ents = [doc.ents for doc in docs]
for doc, ex in zip(docs, examples):
if self.use_gold_ents:
ents, _ = ex.get_aligned_ents_and_ner()
doc.ents = ents
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
else:
# only keep matching ents
doc.ents = ex.get_matching_ents()
# make sure we have something to learn from, if not, short-circuit
if not self.batch_has_learnable_example(examples):
return losses
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
sentence_encodings, bp_context = self.model.begin_update(docs)
# now restore the ents
for doc, old in zip(docs, old_ents):
doc.ents = old
loss, d_scores = self.get_loss(
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
sentence_encodings=sentence_encodings, examples=examples
)
bp_context(d_scores)
if sgd is not None:
2020-10-05 17:23:33 +03:00
self.finish_update(sgd)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
losses[self.name] += loss
return losses
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167) * 🚨 Ignore all existing Mypy errors * 🏗 Add Mypy check to CI * Add types-mock and types-requests as dev requirements * Add additional type ignore directives * Add types packages to dev-only list in reqs test * Add types-dataclasses for python 3.6 * Add ignore to pretrain * 🏷 Improve type annotation on `run_command` helper The `run_command` helper previously declared that it returned an `Optional[subprocess.CompletedProcess]`, but it isn't actually possible for the function to return `None`. These changes modify the type annotation of the `run_command` helper and remove all now-unnecessary `# type: ignore` directives. * 🔧 Allow variable type redefinition in limited contexts These changes modify how Mypy is configured to allow variables to have their type automatically redefined under certain conditions. The Mypy documentation contains the following example: ```python def process(items: List[str]) -> None: # 'items' has type List[str] items = [item.split() for item in items] # 'items' now has type List[List[str]] ... ``` This configuration change is especially helpful in reducing the number of `# type: ignore` directives needed to handle the common pattern of: * Accepting a filepath as a string * Overwriting the variable using `filepath = ensure_path(filepath)` These changes enable redefinition and remove all `# type: ignore` directives rendered redundant by this change. * 🏷 Add type annotation to converters mapping * 🚨 Fix Mypy error in convert CLI argument verification * 🏷 Improve type annotation on `resolve_dot_names` helper * 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors` * 🏷 Add type annotations for more `Vocab` attributes * 🏷 Add loose type annotation for gold data compilation * 🏷 Improve `_format_labels` type annotation * 🏷 Fix `get_lang_class` type annotation * 🏷 Loosen return type of `Language.evaluate` * 🏷 Don't accept `Scorer` in `handle_scores_per_type` * 🏷 Add `string_to_list` overloads * 🏷 Fix non-Optional command-line options * 🙈 Ignore redefinition of `wandb_logger` in `loggers.py` * ➕ Install `typing_extensions` in Python 3.8+ The `typing_extensions` package states that it should be used when "writing code that must be compatible with multiple Python versions". Since SpaCy needs to support multiple Python versions, it should be used when newer `typing` module members are required. One example of this is `Literal`, which is available starting with Python 3.8. Previously SpaCy tried to import `Literal` from `typing`, falling back to `typing_extensions` if the import failed. However, Mypy doesn't seem to be able to understand what `Literal` means when the initial import means. Therefore, these changes modify how `compat` imports `Literal` by always importing it from `typing_extensions`. These changes also modify how `typing_extensions` is installed, so that it is a requirement for all Python versions, including those greater than or equal to 3.8. * 🏷 Improve type annotation for `Language.pipe` These changes add a missing overload variant to the type signature of `Language.pipe`. Additionally, the type signature is enhanced to allow type checkers to differentiate between the two overload variants based on the `as_tuple` parameter. Fixes #8772 * ➖ Don't install `typing-extensions` in Python 3.8+ After more detailed analysis of how to implement Python version-specific type annotations using SpaCy, it has been determined that by branching on a comparison against `sys.version_info` can be statically analyzed by Mypy well enough to enable us to conditionally use `typing_extensions.Literal`. This means that we no longer need to install `typing_extensions` for Python versions greater than or equal to 3.8! 🎉 These changes revert previous changes installing `typing-extensions` regardless of Python version and modify how we import the `Literal` type to ensure that Mypy treats it properly. * resolve mypy errors for Strict pydantic types * refactor code to avoid missing return statement * fix types of convert CLI command * avoid list-set confustion in debug_data * fix typo and formatting * small fixes to avoid type ignores * fix types in profile CLI command and make it more efficient * type fixes in projects CLI * put one ignore back * type fixes for render * fix render types - the sequel * fix BaseDefault in language definitions * fix type of noun_chunks iterator - yields tuple instead of span * fix types in language-specific modules * 🏷 Expand accepted inputs of `get_string_id` `get_string_id` accepts either a string (in which case it returns its ID) or an ID (in which case it immediately returns the ID). These changes extend the type annotation of `get_string_id` to indicate that it can accept either strings or IDs. * 🏷 Handle override types in `combine_score_weights` The `combine_score_weights` function allows users to pass an `overrides` mapping to override data extracted from the `weights` argument. Since it allows `Optional` dictionary values, the return value may also include `Optional` dictionary values. These changes update the type annotations for `combine_score_weights` to reflect this fact. * 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer` * 🏷 Fix redefinition of `wandb_logger` These changes fix the redefinition of `wandb_logger` by giving a separate name to each `WandbLogger` version. For backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` as `wandb_logger` for now. * more fixes for typing in language * type fixes in model definitions * 🏷 Annotate `_RandomWords.probs` as `NDArray` * 🏷 Annotate `tok2vec` layers to help Mypy * 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6 Also remove an import that I forgot to move to the top of the module 😅 * more fixes for matchers and other pipeline components * quick fix for entity linker * fixing types for spancat, textcat, etc * bugfix for tok2vec * type annotations for scorer * add runtime_checkable for Protocol * type and import fixes in tests * mypy fixes for training utilities * few fixes in util * fix import * 🐵 Remove unused `# type: ignore` directives * 🏷 Annotate `Language._components` * 🏷 Annotate `spacy.pipeline.Pipe` * add doc as property to span.pyi * small fixes and cleanup * explicit type annotations instead of via comment Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 16:21:40 +03:00
def get_loss(self, examples: Iterable[Example], sentence_encodings: Floats2d):
validate_examples(examples, "EntityLinker.get_loss")
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
entity_encodings = []
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
eidx = 0 # indices in gold entities to keep
keep_ents = [] # indices in sentence_encodings to keep
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
for eg in examples:
kb_ids = eg.get_aligned("ENT_KB_ID", as_string=True)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
for ent in eg.get_matching_ents():
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
kb_id = kb_ids[ent.start]
if kb_id:
entity_encoding = self.kb.get_vector(kb_id)
entity_encodings.append(entity_encoding)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
keep_ents.append(eidx)
eidx += 1
entity_encodings = self.model.ops.asarray2f(entity_encodings, dtype="float32")
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
selected_encodings = sentence_encodings[keep_ents]
# if there are no matches, short circuit
if not keep_ents:
out = self.model.ops.alloc2f(*sentence_encodings.shape)
return 0, out
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
if selected_encodings.shape != entity_encodings.shape:
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
err = Errors.E147.format(
method="get_loss", msg="gold entities do not match up"
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
)
raise RuntimeError(err)
gradients = self.distance.get_grad(selected_encodings, entity_encodings)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
# to match the input size, we need to give a zero gradient for items not in the kb
out = self.model.ops.alloc2f(*sentence_encodings.shape)
out[keep_ents] = gradients
loss = self.distance.get_loss(selected_encodings, entity_encodings)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
loss = loss / len(entity_encodings)
Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <svlandeg@github.com>
2022-03-04 11:17:36 +03:00
return float(loss), out
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
def predict(self, docs: Iterable[Doc]) -> List[str]:
"""Apply the pipeline's model to a batch of docs, without modifying them.
Returns the KB IDs for each entity in each doc, including NIL if there is
no prediction.
docs (Iterable[Doc]): The documents to predict.
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167) * 🚨 Ignore all existing Mypy errors * 🏗 Add Mypy check to CI * Add types-mock and types-requests as dev requirements * Add additional type ignore directives * Add types packages to dev-only list in reqs test * Add types-dataclasses for python 3.6 * Add ignore to pretrain * 🏷 Improve type annotation on `run_command` helper The `run_command` helper previously declared that it returned an `Optional[subprocess.CompletedProcess]`, but it isn't actually possible for the function to return `None`. These changes modify the type annotation of the `run_command` helper and remove all now-unnecessary `# type: ignore` directives. * 🔧 Allow variable type redefinition in limited contexts These changes modify how Mypy is configured to allow variables to have their type automatically redefined under certain conditions. The Mypy documentation contains the following example: ```python def process(items: List[str]) -> None: # 'items' has type List[str] items = [item.split() for item in items] # 'items' now has type List[List[str]] ... ``` This configuration change is especially helpful in reducing the number of `# type: ignore` directives needed to handle the common pattern of: * Accepting a filepath as a string * Overwriting the variable using `filepath = ensure_path(filepath)` These changes enable redefinition and remove all `# type: ignore` directives rendered redundant by this change. * 🏷 Add type annotation to converters mapping * 🚨 Fix Mypy error in convert CLI argument verification * 🏷 Improve type annotation on `resolve_dot_names` helper * 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors` * 🏷 Add type annotations for more `Vocab` attributes * 🏷 Add loose type annotation for gold data compilation * 🏷 Improve `_format_labels` type annotation * 🏷 Fix `get_lang_class` type annotation * 🏷 Loosen return type of `Language.evaluate` * 🏷 Don't accept `Scorer` in `handle_scores_per_type` * 🏷 Add `string_to_list` overloads * 🏷 Fix non-Optional command-line options * 🙈 Ignore redefinition of `wandb_logger` in `loggers.py` * ➕ Install `typing_extensions` in Python 3.8+ The `typing_extensions` package states that it should be used when "writing code that must be compatible with multiple Python versions". Since SpaCy needs to support multiple Python versions, it should be used when newer `typing` module members are required. One example of this is `Literal`, which is available starting with Python 3.8. Previously SpaCy tried to import `Literal` from `typing`, falling back to `typing_extensions` if the import failed. However, Mypy doesn't seem to be able to understand what `Literal` means when the initial import means. Therefore, these changes modify how `compat` imports `Literal` by always importing it from `typing_extensions`. These changes also modify how `typing_extensions` is installed, so that it is a requirement for all Python versions, including those greater than or equal to 3.8. * 🏷 Improve type annotation for `Language.pipe` These changes add a missing overload variant to the type signature of `Language.pipe`. Additionally, the type signature is enhanced to allow type checkers to differentiate between the two overload variants based on the `as_tuple` parameter. Fixes #8772 * ➖ Don't install `typing-extensions` in Python 3.8+ After more detailed analysis of how to implement Python version-specific type annotations using SpaCy, it has been determined that by branching on a comparison against `sys.version_info` can be statically analyzed by Mypy well enough to enable us to conditionally use `typing_extensions.Literal`. This means that we no longer need to install `typing_extensions` for Python versions greater than or equal to 3.8! 🎉 These changes revert previous changes installing `typing-extensions` regardless of Python version and modify how we import the `Literal` type to ensure that Mypy treats it properly. * resolve mypy errors for Strict pydantic types * refactor code to avoid missing return statement * fix types of convert CLI command * avoid list-set confustion in debug_data * fix typo and formatting * small fixes to avoid type ignores * fix types in profile CLI command and make it more efficient * type fixes in projects CLI * put one ignore back * type fixes for render * fix render types - the sequel * fix BaseDefault in language definitions * fix type of noun_chunks iterator - yields tuple instead of span * fix types in language-specific modules * 🏷 Expand accepted inputs of `get_string_id` `get_string_id` accepts either a string (in which case it returns its ID) or an ID (in which case it immediately returns the ID). These changes extend the type annotation of `get_string_id` to indicate that it can accept either strings or IDs. * 🏷 Handle override types in `combine_score_weights` The `combine_score_weights` function allows users to pass an `overrides` mapping to override data extracted from the `weights` argument. Since it allows `Optional` dictionary values, the return value may also include `Optional` dictionary values. These changes update the type annotations for `combine_score_weights` to reflect this fact. * 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer` * 🏷 Fix redefinition of `wandb_logger` These changes fix the redefinition of `wandb_logger` by giving a separate name to each `WandbLogger` version. For backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` as `wandb_logger` for now. * more fixes for typing in language * type fixes in model definitions * 🏷 Annotate `_RandomWords.probs` as `NDArray` * 🏷 Annotate `tok2vec` layers to help Mypy * 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6 Also remove an import that I forgot to move to the top of the module 😅 * more fixes for matchers and other pipeline components * quick fix for entity linker * fixing types for spancat, textcat, etc * bugfix for tok2vec * type annotations for scorer * add runtime_checkable for Protocol * type and import fixes in tests * mypy fixes for training utilities * few fixes in util * fix import * 🐵 Remove unused `# type: ignore` directives * 🏷 Annotate `Language._components` * 🏷 Annotate `spacy.pipeline.Pipe` * add doc as property to span.pyi * small fixes and cleanup * explicit type annotations instead of via comment Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 16:21:40 +03:00
RETURNS (List[str]): The models prediction for each document.
DOCS: https://spacy.io/api/entitylinker#predict
"""
self.validate_kb()
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
entity_count = 0
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167) * 🚨 Ignore all existing Mypy errors * 🏗 Add Mypy check to CI * Add types-mock and types-requests as dev requirements * Add additional type ignore directives * Add types packages to dev-only list in reqs test * Add types-dataclasses for python 3.6 * Add ignore to pretrain * 🏷 Improve type annotation on `run_command` helper The `run_command` helper previously declared that it returned an `Optional[subprocess.CompletedProcess]`, but it isn't actually possible for the function to return `None`. These changes modify the type annotation of the `run_command` helper and remove all now-unnecessary `# type: ignore` directives. * 🔧 Allow variable type redefinition in limited contexts These changes modify how Mypy is configured to allow variables to have their type automatically redefined under certain conditions. The Mypy documentation contains the following example: ```python def process(items: List[str]) -> None: # 'items' has type List[str] items = [item.split() for item in items] # 'items' now has type List[List[str]] ... ``` This configuration change is especially helpful in reducing the number of `# type: ignore` directives needed to handle the common pattern of: * Accepting a filepath as a string * Overwriting the variable using `filepath = ensure_path(filepath)` These changes enable redefinition and remove all `# type: ignore` directives rendered redundant by this change. * 🏷 Add type annotation to converters mapping * 🚨 Fix Mypy error in convert CLI argument verification * 🏷 Improve type annotation on `resolve_dot_names` helper * 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors` * 🏷 Add type annotations for more `Vocab` attributes * 🏷 Add loose type annotation for gold data compilation * 🏷 Improve `_format_labels` type annotation * 🏷 Fix `get_lang_class` type annotation * 🏷 Loosen return type of `Language.evaluate` * 🏷 Don't accept `Scorer` in `handle_scores_per_type` * 🏷 Add `string_to_list` overloads * 🏷 Fix non-Optional command-line options * 🙈 Ignore redefinition of `wandb_logger` in `loggers.py` * ➕ Install `typing_extensions` in Python 3.8+ The `typing_extensions` package states that it should be used when "writing code that must be compatible with multiple Python versions". Since SpaCy needs to support multiple Python versions, it should be used when newer `typing` module members are required. One example of this is `Literal`, which is available starting with Python 3.8. Previously SpaCy tried to import `Literal` from `typing`, falling back to `typing_extensions` if the import failed. However, Mypy doesn't seem to be able to understand what `Literal` means when the initial import means. Therefore, these changes modify how `compat` imports `Literal` by always importing it from `typing_extensions`. These changes also modify how `typing_extensions` is installed, so that it is a requirement for all Python versions, including those greater than or equal to 3.8. * 🏷 Improve type annotation for `Language.pipe` These changes add a missing overload variant to the type signature of `Language.pipe`. Additionally, the type signature is enhanced to allow type checkers to differentiate between the two overload variants based on the `as_tuple` parameter. Fixes #8772 * ➖ Don't install `typing-extensions` in Python 3.8+ After more detailed analysis of how to implement Python version-specific type annotations using SpaCy, it has been determined that by branching on a comparison against `sys.version_info` can be statically analyzed by Mypy well enough to enable us to conditionally use `typing_extensions.Literal`. This means that we no longer need to install `typing_extensions` for Python versions greater than or equal to 3.8! 🎉 These changes revert previous changes installing `typing-extensions` regardless of Python version and modify how we import the `Literal` type to ensure that Mypy treats it properly. * resolve mypy errors for Strict pydantic types * refactor code to avoid missing return statement * fix types of convert CLI command * avoid list-set confustion in debug_data * fix typo and formatting * small fixes to avoid type ignores * fix types in profile CLI command and make it more efficient * type fixes in projects CLI * put one ignore back * type fixes for render * fix render types - the sequel * fix BaseDefault in language definitions * fix type of noun_chunks iterator - yields tuple instead of span * fix types in language-specific modules * 🏷 Expand accepted inputs of `get_string_id` `get_string_id` accepts either a string (in which case it returns its ID) or an ID (in which case it immediately returns the ID). These changes extend the type annotation of `get_string_id` to indicate that it can accept either strings or IDs. * 🏷 Handle override types in `combine_score_weights` The `combine_score_weights` function allows users to pass an `overrides` mapping to override data extracted from the `weights` argument. Since it allows `Optional` dictionary values, the return value may also include `Optional` dictionary values. These changes update the type annotations for `combine_score_weights` to reflect this fact. * 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer` * 🏷 Fix redefinition of `wandb_logger` These changes fix the redefinition of `wandb_logger` by giving a separate name to each `WandbLogger` version. For backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` as `wandb_logger` for now. * more fixes for typing in language * type fixes in model definitions * 🏷 Annotate `_RandomWords.probs` as `NDArray` * 🏷 Annotate `tok2vec` layers to help Mypy * 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6 Also remove an import that I forgot to move to the top of the module 😅 * more fixes for matchers and other pipeline components * quick fix for entity linker * fixing types for spancat, textcat, etc * bugfix for tok2vec * type annotations for scorer * add runtime_checkable for Protocol * type and import fixes in tests * mypy fixes for training utilities * few fixes in util * fix import * 🐵 Remove unused `# type: ignore` directives * 🏷 Annotate `Language._components` * 🏷 Annotate `spacy.pipeline.Pipe` * add doc as property to span.pyi * small fixes and cleanup * explicit type annotations instead of via comment Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 16:21:40 +03:00
final_kb_ids: List[str] = []
xp = self.model.ops.xp
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
if not docs:
return final_kb_ids
if isinstance(docs, Doc):
docs = [docs]
for i, doc in enumerate(docs):
if len(doc) == 0:
continue
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
sentences = [s for s in doc.sents]
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
# Loop over entities in batches.
for ent_idx in range(0, len(doc.ents), self.candidates_batch_size):
ent_batch = doc.ents[ent_idx : ent_idx + self.candidates_batch_size]
# Look up candidate entities.
valid_ent_idx = [
idx
for idx in range(len(ent_batch))
if ent_batch[idx].label_ not in self.labels_discard
]
batch_candidates = list(
self.get_candidates_batch(
self.kb, [ent_batch[idx] for idx in valid_ent_idx]
)
if self.candidates_batch_size > 1
else [
self.get_candidates(self.kb, ent_batch[idx])
for idx in valid_ent_idx
]
)
# Looping through each entity in batch (TODO: rewrite)
for j, ent in enumerate(ent_batch):
assert hasattr(ent, "sents")
sents = list(ent.sents)
sent_indices = (
sentences.index(sents[0]),
sentences.index(sents[-1]),
)
assert sent_indices[1] >= sent_indices[0] >= 0
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
if self.incl_context:
# get n_neighbour sentences, clipped to the length of the document
start_sentence = max(0, sent_indices[0] - self.n_sents)
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
end_sentence = min(
len(sentences) - 1, sent_indices[1] + self.n_sents
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
)
start_token = sentences[start_sentence].start
end_token = sentences[end_sentence].end
sent_doc = doc[start_token:end_token].as_doc()
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
# currently, the context is the same for each entity in a sentence (should be refined)
sentence_encoding = self.model.predict([sent_doc])[0]
sentence_encoding_t = sentence_encoding.T
sentence_norm = xp.linalg.norm(sentence_encoding_t)
entity_count += 1
if ent.label_ in self.labels_discard:
# ignoring this entity - setting to NIL
final_kb_ids.append(self.NIL)
else:
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
candidates = list(batch_candidates[j])
if not candidates:
# no prediction possible for this entity - setting to NIL
final_kb_ids.append(self.NIL)
elif len(candidates) == 1 and self.threshold is None:
# shortcut for efficiency reasons: take the 1 candidate
final_kb_ids.append(candidates[0].entity_)
else:
random.shuffle(candidates)
# set all prior probabilities to 0 if incl_prior=False
prior_probs = xp.asarray([c.prior_prob for c in candidates])
if not self.incl_prior:
prior_probs = xp.asarray([0.0 for _ in candidates])
scores = prior_probs
# add in similarity from the context
if self.incl_context:
entity_encodings = xp.asarray(
[c.entity_vector for c in candidates]
)
entity_norm = xp.linalg.norm(entity_encodings, axis=1)
if len(entity_encodings) != len(prior_probs):
raise RuntimeError(
Errors.E147.format(
method="predict",
msg="vectors not of equal length",
)
)
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
# cosine similarity
sims = xp.dot(entity_encodings, sentence_encoding_t) / (
sentence_norm * entity_norm
2021-06-28 12:48:00 +03:00
)
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
if sims.shape != prior_probs.shape:
raise ValueError(Errors.E161)
scores = prior_probs + sims - (prior_probs * sims)
final_kb_ids.append(
candidates[scores.argmax().item()].entity_
if self.threshold is None
or scores.max() >= self.threshold
else EntityLinker.NIL
)
Refactor KB for easier customization (#11268) * Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups. * Fix tests. Add distinction w.r.t. batch size. * Remove redundant and add new comments. * Adjust comments. Fix variable naming in EL prediction. * Fix mypy errors. * Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues. * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/kb_base.pyx Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Update spacy/pipeline/entity_linker.py Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Add error messages to NotImplementedErrors. Remove redundant comment. * Fix imports. * Remove redundant comments. * Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase. * Fix tests. * Update spacy/errors.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Move KB into subdirectory. * Adjust imports after KB move to dedicated subdirectory. * Fix config imports. * Move Candidate + retrieval functions to separate module. Fix other, small issues. * Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions. * Update spacy/kb/kb_in_memory.pyx Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/ml/models/entity_linker.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typing. * Change typing of mentions to be Span instead of Union[Span, str]. * Update docs. * Update EntityLinker and _architecture docs. * Update website/docs/api/entitylinker.md Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> * Adjust message for E1046. * Re-add section for Candidate in kb.md, add reference to dedicated page. * Update docs and docstrings. * Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs. * Update spacy/kb/candidate.pyx * Update spacy/kb/kb_in_memory.pyx * Update spacy/pipeline/legacy/entity_linker.py * Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py. Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-09-08 11:38:07 +03:00
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
if not (len(final_kb_ids) == entity_count):
err = Errors.E147.format(
method="predict", msg="result variables not of equal length"
)
raise RuntimeError(err)
return final_kb_ids
def set_annotations(self, docs: Iterable[Doc], kb_ids: List[str]) -> None:
"""Modify a batch of documents, using pre-computed scores.
docs (Iterable[Doc]): The documents to modify.
kb_ids (List[str]): The IDs to set, produced by EntityLinker.predict.
DOCS: https://spacy.io/api/entitylinker#set_annotations
"""
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
count_ents = len([ent for doc in docs for ent in doc.ents])
if count_ents != len(kb_ids):
raise ValueError(Errors.E148.format(ents=count_ents, ids=len(kb_ids)))
i = 0
overwrite = self.cfg["overwrite"]
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
for doc in docs:
for ent in doc.ents:
kb_id = kb_ids[i]
i += 1
for token in ent:
if token.ent_kb_id == 0 or overwrite:
token.ent_kb_id_ = kb_id
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
def to_bytes(self, *, exclude=tuple()):
"""Serialize the pipe to a bytestring.
exclude (Iterable[str]): String names of serialization fields to exclude.
RETURNS (bytes): The serialized object.
DOCS: https://spacy.io/api/entitylinker#to_bytes
"""
self._validate_serialization_attrs()
serialize = {}
if hasattr(self, "cfg") and self.cfg is not None:
serialize["cfg"] = lambda: srsly.json_dumps(self.cfg)
serialize["vocab"] = lambda: self.vocab.to_bytes(exclude=exclude)
serialize["kb"] = self.kb.to_bytes
serialize["model"] = self.model.to_bytes
return util.to_bytes(serialize, exclude)
def from_bytes(self, bytes_data, *, exclude=tuple()):
"""Load the pipe from a bytestring.
exclude (Iterable[str]): String names of serialization fields to exclude.
RETURNS (TrainablePipe): The loaded object.
DOCS: https://spacy.io/api/entitylinker#from_bytes
"""
self._validate_serialization_attrs()
def load_model(b):
try:
self.model.from_bytes(b)
except AttributeError:
raise ValueError(Errors.E149) from None
deserialize = {}
if hasattr(self, "cfg") and self.cfg is not None:
deserialize["cfg"] = lambda b: self.cfg.update(srsly.json_loads(b))
deserialize["vocab"] = lambda b: self.vocab.from_bytes(b, exclude=exclude)
deserialize["kb"] = lambda b: self.kb.from_bytes(b)
deserialize["model"] = load_model
util.from_bytes(bytes_data, deserialize, exclude)
return self
2020-07-29 16:14:07 +03:00
def to_disk(
self, path: Union[str, Path], *, exclude: Iterable[str] = SimpleFrozenList()
2020-07-29 16:14:07 +03:00
) -> None:
"""Serialize the pipe to disk.
path (str / Path): Path to a directory.
exclude (Iterable[str]): String names of serialization fields to exclude.
DOCS: https://spacy.io/api/entitylinker#to_disk
"""
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
serialize = {}
serialize["vocab"] = lambda p: self.vocab.to_disk(p, exclude=exclude)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
serialize["cfg"] = lambda p: srsly.write_json(p, self.cfg)
serialize["kb"] = lambda p: self.kb.to_disk(p)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
serialize["model"] = lambda p: self.model.to_disk(p)
util.to_disk(path, serialize, exclude)
def from_disk(
self, path: Union[str, Path], *, exclude: Iterable[str] = SimpleFrozenList()
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
) -> "EntityLinker":
"""Load the pipe from disk. Modifies the object in place and returns it.
path (str / Path): Path to a directory.
exclude (Iterable[str]): String names of serialization fields to exclude.
RETURNS (EntityLinker): The modified EntityLinker object.
DOCS: https://spacy.io/api/entitylinker#from_disk
"""
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
def load_model(p):
try:
with p.open("rb") as infile:
self.model.from_bytes(infile.read())
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
except AttributeError:
raise ValueError(Errors.E149) from None
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167) * 🚨 Ignore all existing Mypy errors * 🏗 Add Mypy check to CI * Add types-mock and types-requests as dev requirements * Add additional type ignore directives * Add types packages to dev-only list in reqs test * Add types-dataclasses for python 3.6 * Add ignore to pretrain * 🏷 Improve type annotation on `run_command` helper The `run_command` helper previously declared that it returned an `Optional[subprocess.CompletedProcess]`, but it isn't actually possible for the function to return `None`. These changes modify the type annotation of the `run_command` helper and remove all now-unnecessary `# type: ignore` directives. * 🔧 Allow variable type redefinition in limited contexts These changes modify how Mypy is configured to allow variables to have their type automatically redefined under certain conditions. The Mypy documentation contains the following example: ```python def process(items: List[str]) -> None: # 'items' has type List[str] items = [item.split() for item in items] # 'items' now has type List[List[str]] ... ``` This configuration change is especially helpful in reducing the number of `# type: ignore` directives needed to handle the common pattern of: * Accepting a filepath as a string * Overwriting the variable using `filepath = ensure_path(filepath)` These changes enable redefinition and remove all `# type: ignore` directives rendered redundant by this change. * 🏷 Add type annotation to converters mapping * 🚨 Fix Mypy error in convert CLI argument verification * 🏷 Improve type annotation on `resolve_dot_names` helper * 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors` * 🏷 Add type annotations for more `Vocab` attributes * 🏷 Add loose type annotation for gold data compilation * 🏷 Improve `_format_labels` type annotation * 🏷 Fix `get_lang_class` type annotation * 🏷 Loosen return type of `Language.evaluate` * 🏷 Don't accept `Scorer` in `handle_scores_per_type` * 🏷 Add `string_to_list` overloads * 🏷 Fix non-Optional command-line options * 🙈 Ignore redefinition of `wandb_logger` in `loggers.py` * ➕ Install `typing_extensions` in Python 3.8+ The `typing_extensions` package states that it should be used when "writing code that must be compatible with multiple Python versions". Since SpaCy needs to support multiple Python versions, it should be used when newer `typing` module members are required. One example of this is `Literal`, which is available starting with Python 3.8. Previously SpaCy tried to import `Literal` from `typing`, falling back to `typing_extensions` if the import failed. However, Mypy doesn't seem to be able to understand what `Literal` means when the initial import means. Therefore, these changes modify how `compat` imports `Literal` by always importing it from `typing_extensions`. These changes also modify how `typing_extensions` is installed, so that it is a requirement for all Python versions, including those greater than or equal to 3.8. * 🏷 Improve type annotation for `Language.pipe` These changes add a missing overload variant to the type signature of `Language.pipe`. Additionally, the type signature is enhanced to allow type checkers to differentiate between the two overload variants based on the `as_tuple` parameter. Fixes #8772 * ➖ Don't install `typing-extensions` in Python 3.8+ After more detailed analysis of how to implement Python version-specific type annotations using SpaCy, it has been determined that by branching on a comparison against `sys.version_info` can be statically analyzed by Mypy well enough to enable us to conditionally use `typing_extensions.Literal`. This means that we no longer need to install `typing_extensions` for Python versions greater than or equal to 3.8! 🎉 These changes revert previous changes installing `typing-extensions` regardless of Python version and modify how we import the `Literal` type to ensure that Mypy treats it properly. * resolve mypy errors for Strict pydantic types * refactor code to avoid missing return statement * fix types of convert CLI command * avoid list-set confustion in debug_data * fix typo and formatting * small fixes to avoid type ignores * fix types in profile CLI command and make it more efficient * type fixes in projects CLI * put one ignore back * type fixes for render * fix render types - the sequel * fix BaseDefault in language definitions * fix type of noun_chunks iterator - yields tuple instead of span * fix types in language-specific modules * 🏷 Expand accepted inputs of `get_string_id` `get_string_id` accepts either a string (in which case it returns its ID) or an ID (in which case it immediately returns the ID). These changes extend the type annotation of `get_string_id` to indicate that it can accept either strings or IDs. * 🏷 Handle override types in `combine_score_weights` The `combine_score_weights` function allows users to pass an `overrides` mapping to override data extracted from the `weights` argument. Since it allows `Optional` dictionary values, the return value may also include `Optional` dictionary values. These changes update the type annotations for `combine_score_weights` to reflect this fact. * 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer` * 🏷 Fix redefinition of `wandb_logger` These changes fix the redefinition of `wandb_logger` by giving a separate name to each `WandbLogger` version. For backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` as `wandb_logger` for now. * more fixes for typing in language * type fixes in model definitions * 🏷 Annotate `_RandomWords.probs` as `NDArray` * 🏷 Annotate `tok2vec` layers to help Mypy * 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6 Also remove an import that I forgot to move to the top of the module 😅 * more fixes for matchers and other pipeline components * quick fix for entity linker * fixing types for spancat, textcat, etc * bugfix for tok2vec * type annotations for scorer * add runtime_checkable for Protocol * type and import fixes in tests * mypy fixes for training utilities * few fixes in util * fix import * 🐵 Remove unused `# type: ignore` directives * 🏷 Annotate `Language._components` * 🏷 Annotate `spacy.pipeline.Pipe` * add doc as property to span.pyi * small fixes and cleanup * explicit type annotations instead of via comment Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 16:21:40 +03:00
deserialize: Dict[str, Callable[[Any], Any]] = {}
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
deserialize["cfg"] = lambda p: self.cfg.update(deserialize_config(p))
deserialize["vocab"] = lambda p: self.vocab.from_disk(p, exclude=exclude)
deserialize["kb"] = lambda p: self.kb.from_disk(p)
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
deserialize["model"] = load_model
util.from_disk(path, deserialize, exclude)
return self
def rehearse(self, examples, *, sgd=None, losses=None, **config):
Refactor pipeline components, config and language data (#5759) * Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 14:42:59 +03:00
raise NotImplementedError
def add_label(self, label):
raise NotImplementedError