mirror of
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d33953037e
* Create aryaprabhudesai.md (#2681) * Update _install.jade (#2688) Typo fix: "models" -> "model" * Add FAC to spacy.explain (resolves #2706) * Remove docstrings for deprecated arguments (see #2703) * When calling getoption() in conftest.py, pass a default option (#2709) * When calling getoption() in conftest.py, pass a default option This is necessary to allow testing an installed spacy by running: pytest --pyargs spacy * Add contributor agreement * update bengali token rules for hyphen and digits (#2731) * Less norm computations in token similarity (#2730) * Less norm computations in token similarity * Contributor agreement * Remove ')' for clarity (#2737) Sorry, don't mean to be nitpicky, I just noticed this when going through the CLI and thought it was a quick fix. That said, if this was intention than please let me know. * added contributor agreement for mbkupfer (#2738) * Basic support for Telugu language (#2751) * Lex _attrs for polish language (#2750) * Signed spaCy contributor agreement * Added polish version of english lex_attrs * Introduces a bulk merge function, in order to solve issue #653 (#2696) * Fix comment * Introduce bulk merge to increase performance on many span merges * Sign contributor agreement * Implement pull request suggestions * Describe converters more explicitly (see #2643) * Add multi-threading note to Language.pipe (resolves #2582) [ci skip] * Fix formatting * Fix dependency scheme docs (closes #2705) [ci skip] * Don't set stop word in example (closes #2657) [ci skip] * Add words to portuguese language _num_words (#2759) * Add words to portuguese language _num_words * Add words to portuguese language _num_words * Update Indonesian model (#2752) * adding e-KTP in tokenizer exceptions list * add exception token * removing lines with containing space as it won't matter since we use .split() method in the end, added new tokens in exception * add tokenizer exceptions list * combining base_norms with norm_exceptions * adding norm_exception * fix double key in lemmatizer * remove unused import on punctuation.py * reformat stop_words to reduce number of lines, improve readibility * updating tokenizer exception * implement is_currency for lang/id * adding orth_first_upper in tokenizer_exceptions * update the norm_exception list * remove bunch of abbreviations * adding contributors file * Fixed spaCy+Keras example (#2763) * bug fixes in keras example * created contributor agreement * Adding French hyphenated first name (#2786) * Fix typo (closes #2784) * Fix typo (#2795) [ci skip] Fixed typo on line 6 "regcognizer --> recognizer" * Adding basic support for Sinhala language. (#2788) * adding Sinhala language package, stop words, examples and lex_attrs. * Adding contributor agreement * Updating contributor agreement * Also include lowercase norm exceptions * Fix error (#2802) * Fix error ValueError: cannot resize an array that references or is referenced by another array in this way. Use the resize function * added spaCy Contributor Agreement * Add charlax's contributor agreement (#2805) * agreement of contributor, may I introduce a tiny pl languge contribution (#2799) * Contributors agreement * Contributors agreement * Contributors agreement * Add jupyter=True to displacy.render in documentation (#2806) * Revert "Also include lowercase norm exceptions" This reverts commit70f4e8adf3
. * Remove deprecated encoding argument to msgpack * Set up dependency tree pattern matching skeleton (#2732) * Fix bug when too many entity types. Fixes #2800 * Fix Python 2 test failure * Require older msgpack-numpy * Restore encoding arg on msgpack-numpy * Try to fix version pin for msgpack-numpy * Update Portuguese Language (#2790) * Add words to portuguese language _num_words * Add words to portuguese language _num_words * Portuguese - Add/remove stopwords, fix tokenizer, add currency symbols * Extended punctuation and norm_exceptions in the Portuguese language * Correct error in spacy universe docs concerning spacy-lookup (#2814) * Update Keras Example for (Parikh et al, 2016) implementation (#2803) * bug fixes in keras example * created contributor agreement * baseline for Parikh model * initial version of parikh 2016 implemented * tested asymmetric models * fixed grevious error in normalization * use standard SNLI test file * begin to rework parikh example * initial version of running example * start to document the new version * start to document the new version * Update Decompositional Attention.ipynb * fixed calls to similarity * updated the README * import sys package duh * simplified indexing on mapping word to IDs * stupid python indent error * added code from https://github.com/tensorflow/tensorflow/issues/3388 for tf bug workaround * Fix typo (closes #2815) [ci skip] * Update regex version dependency * Set version to 2.0.13.dev3 * Skip seemingly problematic test * Remove problematic test * Try previous version of regex * Revert "Remove problematic test" This reverts commitbdebbef455
. * Unskip test * Try older version of regex * 💫 Update training examples and use minibatching (#2830) <!--- Provide a general summary of your changes in the title. --> ## Description Update the training examples in `/examples/training` to show usage of spaCy's `minibatch` and `compounding` helpers ([see here](https://spacy.io/usage/training#tips-batch-size) for details). The lack of batching in the examples has caused some confusion in the past, especially for beginners who would copy-paste the examples, update them with large training sets and experienced slow and unsatisfying results. ### Types of change enhancements ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Visual C++ link updated (#2842) (closes #2841) [ci skip] * New landing page * Add contribution agreement * Correcting lang/ru/examples.py (#2845) * Correct some grammatical inaccuracies in lang\ru\examples.py; filled Contributor Agreement * Correct some grammatical inaccuracies in lang\ru\examples.py * Move contributor agreement to separate file * Set version to 2.0.13.dev4 * Add Persian(Farsi) language support (#2797) * Also include lowercase norm exceptions * Remove in favour of https://github.com/explosion/spaCy/graphs/contributors * Rule-based French Lemmatizer (#2818) <!--- Provide a general summary of your changes in the title. --> ## Description <!--- Use this section to describe your changes. If your changes required testing, include information about the testing environment and the tests you ran. If your test fixes a bug reported in an issue, don't forget to include the issue number. If your PR is still a work in progress, that's totally fine – just include a note to let us know. --> Add a rule-based French Lemmatizer following the english one and the excellent PR for [greek language optimizations](https://github.com/explosion/spaCy/pull/2558) to adapt the Lemmatizer class. ### Types of change <!-- What type of change does your PR cover? Is it a bug fix, an enhancement or new feature, or a change to the documentation? --> - Lemma dictionary used can be found [here](http://infolingu.univ-mlv.fr/DonneesLinguistiques/Dictionnaires/telechargement.html), I used the XML version. - Add several files containing exhaustive list of words for each part of speech - Add some lemma rules - Add POS that are not checked in the standard Lemmatizer, i.e PRON, DET, ADV and AUX - Modify the Lemmatizer class to check in lookup table as a last resort if POS not mentionned - Modify the lemmatize function to check in lookup table as a last resort - Init files are updated so the model can support all the functionalities mentioned above - Add words to tokenizer_exceptions_list.py in respect to regex used in tokenizer_exceptions.py ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [X] I have submitted the spaCy Contributor Agreement. - [X] I ran the tests, and all new and existing tests passed. - [X] My changes don't require a change to the documentation, or if they do, I've added all required information. * Set version to 2.0.13 * Fix formatting and consistency * Update docs for new version [ci skip] * Increment version [ci skip] * Add info on wheels [ci skip] * Adding "This is a sentence" example to Sinhala (#2846) * Add wheels badge * Update badge [ci skip] * Update README.rst [ci skip] * Update murmurhash pin * Increment version to 2.0.14.dev0 * Update GPU docs for v2.0.14 * Add wheel to setup_requires * Import prefer_gpu and require_gpu functions from Thinc * Add tests for prefer_gpu() and require_gpu() * Update requirements and setup.py * Workaround bug in thinc require_gpu * Set version to v2.0.14 * Update push-tag script * Unhack prefer_gpu * Require thinc 6.10.6 * Update prefer_gpu and require_gpu docs [ci skip] * Fix specifiers for GPU * Set version to 2.0.14.dev1 * Set version to 2.0.14 * Update Thinc version pin * Increment version * Fix msgpack-numpy version pin * Increment version * Update version to 2.0.16 * Update version [ci skip] * Redundant ')' in the Stop words' example (#2856) <!--- Provide a general summary of your changes in the title. --> ## Description <!--- Use this section to describe your changes. If your changes required testing, include information about the testing environment and the tests you ran. If your test fixes a bug reported in an issue, don't forget to include the issue number. If your PR is still a work in progress, that's totally fine – just include a note to let us know. --> ### Types of change <!-- What type of change does your PR cover? Is it a bug fix, an enhancement or new feature, or a change to the documentation? --> ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [ ] I have submitted the spaCy Contributor Agreement. - [ ] I ran the tests, and all new and existing tests passed. - [ ] My changes don't require a change to the documentation, or if they do, I've added all required information. * Documentation improvement regarding joblib and SO (#2867) Some documentation improvements ## Description 1. Fixed the dead URL to joblib 2. Fixed Stack Overflow brand name (with space) ### Types of change Documentation ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * raise error when setting overlapping entities as doc.ents (#2880) * Fix out-of-bounds access in NER training The helper method state.B(1) gets the index of the first token of the buffer, or -1 if no such token exists. Normally this is safe because we pass this to functions like state.safe_get(), which returns an empty token. Here we used it directly as an array index, which is not okay! This error may have been the cause of out-of-bounds access errors during training. Similar errors may still be around, so much be hunted down. Hunting this one down took a long time...I printed out values across training runs and diffed, looking for points of divergence between runs, when no randomness should be allowed. * Change PyThaiNLP Url (#2876) * Fix missing comma * Add example showing a fix-up rule for space entities * Set version to 2.0.17.dev0 * Update regex version * Revert "Update regex version" This reverts commit62358dd867
. * Try setting older regex version, to align with conda * Set version to 2.0.17 * Add spacy-js to universe [ci-skip] * Add spacy-raspberry to universe (closes #2889) * Add script to validate universe json [ci skip] * Removed space in docs + added contributor indo (#2909) * - removed unneeded space in documentation * - added contributor info * Allow input text of length up to max_length, inclusive (#2922) * Include universe spec for spacy-wordnet component (#2919) * feat: include universe spec for spacy-wordnet component * chore: include spaCy contributor agreement * Minor formatting changes [ci skip] * Fix image [ci skip] Twitter URL doesn't work on live site * Check if the word is in one of the regular lists specific to each POS (#2886) * 💫 Create random IDs for SVGs to prevent ID clashes (#2927) Resolves #2924. ## Description Fixes problem where multiple visualizations in Jupyter notebooks would have clashing arc IDs, resulting in weirdly positioned arc labels. Generating a random ID prefix so even identical parses won't receive the same IDs for consistency (even if effect of ID clash isn't noticable here.) ### Types of change bug fix ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Fix typo [ci skip] * fixes symbolic link on py3 and windows (#2949) * fixes symbolic link on py3 and windows during setup of spacy using command python -m spacy link en_core_web_sm en closes #2948 * Update spacy/compat.py Co-Authored-By: cicorias <cicorias@users.noreply.github.com> * Fix formatting * Update universe [ci skip] * Catalan Language Support (#2940) * Catalan language Support * Ddding Catalan to documentation * Sort languages alphabetically [ci skip] * Update tests for pytest 4.x (#2965) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Replace marks in params for pytest 4.0 compat ([see here](https://docs.pytest.org/en/latest/deprecations.html#marks-in-pytest-mark-parametrize)) - [x] Un-xfail passing tests (some fixes in a recent update resolved a bunch of issues, but tests were apparently never updated here) ### Types of change <!-- What type of change does your PR cover? Is it a bug fix, an enhancement or new feature, or a change to the documentation? --> ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Fix regex pin to harmonize with conda (#2964) * Update README.rst * Fix bug where Vocab.prune_vector did not use 'batch_size' (#2977) Fixes #2976 * Fix typo * Fix typo * Remove duplicate file * Require thinc 7.0.0.dev2 Fixes bug in gpu_ops that would use cupy instead of numpy on CPU * Add missing import * Fix error IDs * Fix tests
282 lines
11 KiB
Cython
282 lines
11 KiB
Cython
# coding: utf8
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# cython: infer_types=True
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# cython: bounds_check=False
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# cython: profile=True
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from __future__ import unicode_literals
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from libc.string cimport memcpy, memset
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from libc.stdlib cimport malloc, free
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from cymem.cymem cimport Pool
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from .doc cimport Doc, set_children_from_heads, token_by_start, token_by_end
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from .span cimport Span
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from .token cimport Token
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from ..lexeme cimport Lexeme, EMPTY_LEXEME
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from ..structs cimport LexemeC, TokenC
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from ..attrs cimport TAG
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from ..attrs import intify_attrs
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from ..util import SimpleFrozenDict
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from ..errors import Errors
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cdef class Retokenizer:
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"""Helper class for doc.retokenize() context manager."""
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cdef Doc doc
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cdef list merges
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cdef list splits
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cdef set tokens_to_merge
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def __init__(self, doc):
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self.doc = doc
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self.merges = []
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self.splits = []
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self.tokens_to_merge = set()
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def merge(self, Span span, attrs=SimpleFrozenDict()):
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"""Mark a span for merging. The attrs will be applied to the resulting
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token.
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"""
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for token in span:
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if token.i in self.tokens_to_merge:
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raise ValueError(Errors.E102.format(token=repr(token)))
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self.tokens_to_merge.add(token.i)
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attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
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self.merges.append((span, attrs))
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def split(self, Token token, orths, attrs=SimpleFrozenDict()):
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"""Mark a Token for splitting, into the specified orths. The attrs
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will be applied to each subtoken.
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"""
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attrs = intify_attrs(attrs, strings_map=self.doc.vocab.strings)
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self.splits.append((token.start_char, orths, attrs))
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def __enter__(self):
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self.merges = []
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self.splits = []
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return self
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def __exit__(self, *args):
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# Do the actual merging here
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if len(self.merges) > 1:
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_bulk_merge(self.doc, self.merges)
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elif len(self.merges) == 1:
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(span, attrs) = self.merges[0]
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start = span.start
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end = span.end
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_merge(self.doc, start, end, attrs)
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for start_char, orths, attrs in self.splits:
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raise NotImplementedError
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def _merge(Doc doc, int start, int end, attributes):
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"""Retokenize the document, such that the span at
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`doc.text[start_idx : end_idx]` is merged into a single token. If
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`start_idx` and `end_idx `do not mark start and end token boundaries,
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the document remains unchanged.
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start_idx (int): Character index of the start of the slice to merge.
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end_idx (int): Character index after the end of the slice to merge.
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**attributes: Attributes to assign to the merged token. By default,
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attributes are inherited from the syntactic root of the span.
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RETURNS (Token): The newly merged token, or `None` if the start and end
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indices did not fall at token boundaries.
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"""
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cdef Span span = doc[start:end]
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cdef int start_char = span.start_char
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cdef int end_char = span.end_char
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# Get LexemeC for newly merged token
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new_orth = ''.join([t.text_with_ws for t in span])
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if span[-1].whitespace_:
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new_orth = new_orth[:-len(span[-1].whitespace_)]
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cdef const LexemeC* lex = doc.vocab.get(doc.mem, new_orth)
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# House the new merged token where it starts
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cdef TokenC* token = &doc.c[start]
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token.spacy = doc.c[end-1].spacy
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for attr_name, attr_value in attributes.items():
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if attr_name == TAG:
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doc.vocab.morphology.assign_tag(token, attr_value)
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else:
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Token.set_struct_attr(token, attr_name, attr_value)
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# Make sure ent_iob remains consistent
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if doc.c[end].ent_iob == 1 and token.ent_iob in (0, 2):
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if token.ent_type == doc.c[end].ent_type:
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token.ent_iob = 3
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else:
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# If they're not the same entity type, let them be two entities
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doc.c[end].ent_iob = 3
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# Begin by setting all the head indices to absolute token positions
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# This is easier to work with for now than the offsets
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# Before thinking of something simpler, beware the case where a
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# dependency bridges over the entity. Here the alignment of the
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# tokens changes.
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span_root = span.root.i
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token.dep = span.root.dep
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# We update token.lex after keeping span root and dep, since
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# setting token.lex will change span.start and span.end properties
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# as it modifies the character offsets in the doc
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token.lex = lex
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for i in range(doc.length):
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doc.c[i].head += i
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# Set the head of the merged token, and its dep relation, from the Span
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token.head = doc.c[span_root].head
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# Adjust deps before shrinking tokens
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# Tokens which point into the merged token should now point to it
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# Subtract the offset from all tokens which point to >= end
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offset = (end - start) - 1
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for i in range(doc.length):
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head_idx = doc.c[i].head
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if start <= head_idx < end:
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doc.c[i].head = start
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elif head_idx >= end:
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doc.c[i].head -= offset
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# Now compress the token array
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for i in range(end, doc.length):
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doc.c[i - offset] = doc.c[i]
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for i in range(doc.length - offset, doc.length):
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memset(&doc.c[i], 0, sizeof(TokenC))
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doc.c[i].lex = &EMPTY_LEXEME
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doc.length -= offset
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for i in range(doc.length):
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# ...And, set heads back to a relative position
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doc.c[i].head -= i
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# Set the left/right children, left/right edges
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set_children_from_heads(doc.c, doc.length)
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# Clear the cached Python objects
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# Return the merged Python object
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return doc[start]
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def _bulk_merge(Doc doc, merges):
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"""Retokenize the document, such that the spans described in 'merges'
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are merged into a single token. This method assumes that the merges
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are in the same order at which they appear in the doc, and that merges
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do not intersect each other in any way.
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merges: Tokens to merge, and corresponding attributes to assign to the
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merged token. By default, attributes are inherited from the
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syntactic root of the span.
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RETURNS (Token): The first newly merged token.
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"""
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cdef Span span
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cdef const LexemeC* lex
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cdef Pool mem = Pool()
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tokens = <TokenC**>mem.alloc(len(merges), sizeof(TokenC))
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spans = []
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def _get_start(merge):
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return merge[0].start
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merges.sort(key=_get_start)
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for merge_index, (span, attributes) in enumerate(merges):
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start = span.start
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end = span.end
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spans.append(span)
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# House the new merged token where it starts
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token = &doc.c[start]
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tokens[merge_index] = token
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# Assign attributes
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for attr_name, attr_value in attributes.items():
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if attr_name == TAG:
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doc.vocab.morphology.assign_tag(token, attr_value)
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else:
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Token.set_struct_attr(token, attr_name, attr_value)
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# Memorize span roots and sets dependencies of the newly merged
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# tokens to the dependencies of their roots.
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span_roots = []
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for i, span in enumerate(spans):
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span_roots.append(span.root.i)
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tokens[i].dep = span.root.dep
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# We update token.lex after keeping span root and dep, since
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# setting token.lex will change span.start and span.end properties
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# as it modifies the character offsets in the doc
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for token_index in range(len(merges)):
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new_orth = ''.join([t.text_with_ws for t in spans[token_index]])
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if spans[token_index][-1].whitespace_:
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new_orth = new_orth[:-len(spans[token_index][-1].whitespace_)]
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lex = doc.vocab.get(doc.mem, new_orth)
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tokens[token_index].lex = lex
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# We set trailing space here too
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tokens[token_index].spacy = doc.c[spans[token_index].end-1].spacy
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# Begin by setting all the head indices to absolute token positions
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# This is easier to work with for now than the offsets
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# Before thinking of something simpler, beware the case where a
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# dependency bridges over the entity. Here the alignment of the
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# tokens changes.
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for i in range(doc.length):
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doc.c[i].head += i
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# Set the head of the merged token from the Span
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for i in range(len(merges)):
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tokens[i].head = doc.c[span_roots[i]].head
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# Adjust deps before shrinking tokens
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# Tokens which point into the merged token should now point to it
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# Subtract the offset from all tokens which point to >= end
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offsets = []
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current_span_index = 0
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current_offset = 0
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for i in range(doc.length):
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if current_span_index < len(spans) and i == spans[current_span_index].end:
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#last token was the last of the span
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current_offset += (spans[current_span_index].end - spans[current_span_index].start) -1
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current_span_index += 1
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if current_span_index < len(spans) and \
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spans[current_span_index].start <= i < spans[current_span_index].end:
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offsets.append(spans[current_span_index].start - current_offset)
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else:
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offsets.append(i - current_offset)
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for i in range(doc.length):
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doc.c[i].head = offsets[doc.c[i].head]
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# Now compress the token array
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offset = 0
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in_span = False
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span_index = 0
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for i in range(doc.length):
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if in_span and i == spans[span_index].end:
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# First token after a span
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in_span = False
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span_index += 1
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if span_index < len(spans) and i == spans[span_index].start:
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# First token in a span
|
|
doc.c[i - offset] = doc.c[i] # move token to its place
|
|
offset += (spans[span_index].end - spans[span_index].start) - 1
|
|
in_span = True
|
|
if not in_span:
|
|
doc.c[i - offset] = doc.c[i] # move token to its place
|
|
|
|
for i in range(doc.length - offset, doc.length):
|
|
memset(&doc.c[i], 0, sizeof(TokenC))
|
|
doc.c[i].lex = &EMPTY_LEXEME
|
|
doc.length -= offset
|
|
|
|
# ...And, set heads back to a relative position
|
|
for i in range(doc.length):
|
|
doc.c[i].head -= i
|
|
|
|
# Set the left/right children, left/right edges
|
|
set_children_from_heads(doc.c, doc.length)
|
|
|
|
# Make sure ent_iob remains consistent
|
|
for (span, _) in merges:
|
|
if(span.end < len(offsets)):
|
|
#if it's not the last span
|
|
token_after_span_position = offsets[span.end]
|
|
if doc.c[token_after_span_position].ent_iob == 1\
|
|
and doc.c[token_after_span_position - 1].ent_iob in (0, 2):
|
|
if doc.c[token_after_span_position - 1].ent_type == doc.c[token_after_span_position].ent_type:
|
|
doc.c[token_after_span_position - 1].ent_iob = 3
|
|
else:
|
|
# If they're not the same entity type, let them be two entities
|
|
doc.c[token_after_span_position].ent_iob = 3
|
|
|
|
# Return the merged Python object
|
|
return doc[spans[0].start]
|