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Remove old model shortcuts (#11916)
* Remove old model shortcuts * Remove error, docs warnings about shortcuts * Fix import in util Accidentally deleted the whole import and not just the old part... * Change universe example to v3 style * Switch ubuntu-latest to ubuntu-20.04 in main tests (#11928) * Switch ubuntu-latest to ubuntu-20.04 in main tests * Only use 20.04 for 3.6 * Update some model loading in Universe * Add v2 tag to neuralcoref * Use the spacy-version feature instead of a v2 tag Co-authored-by: svlandeg <svlandeg@github.com>
This commit is contained in:
Paul O'Leary McCann
GitHub
parent
6b9af38eeb
commit
d60997febb
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@ -8,7 +8,6 @@ from ._util import app, Arg, Opt, WHEEL_SUFFIX, SDIST_SUFFIX
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from .. import about
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from ..util import is_package, get_minor_version, run_command
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from ..util import is_prerelease_version
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from ..errors import OLD_MODEL_SHORTCUTS
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@app.command(
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@ -61,12 +60,6 @@ def download(
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version = components[-1]
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else:
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model_name = model
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if model in OLD_MODEL_SHORTCUTS:
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msg.warn(
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f"As of spaCy v3.0, shortcuts like '{model}' are deprecated. Please "
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f"use the full pipeline package name '{OLD_MODEL_SHORTCUTS[model]}' instead."
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)
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model_name = OLD_MODEL_SHORTCUTS[model]
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compatibility = get_compatibility()
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version = get_version(model_name, compatibility)
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@ -720,13 +720,6 @@ class Errors(metaclass=ErrorsWithCodes):
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"method in component '{name}'. If you want to use this "
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"method, make sure it's overwritten on the subclass.")
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E940 = ("Found NaN values in scores.")
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E941 = ("Can't find model '{name}'. It looks like you're trying to load a "
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"model from a shortcut, which is obsolete as of spaCy v3.0. To "
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"load the model, use its full name instead:\n\n"
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"nlp = spacy.load(\"{full}\")\n\nFor more details on the available "
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"models, see the models directory: https://spacy.io/models. If you "
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"want to create a blank model, use spacy.blank: "
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"nlp = spacy.blank(\"{name}\")")
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E942 = ("Executing `after_{name}` callback failed. Expected the function to "
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"return an initialized nlp object but got: {value}. Maybe "
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"you forgot to return the modified object in your function?")
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@ -955,15 +948,6 @@ class Errors(metaclass=ErrorsWithCodes):
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"but got '{received_type}'")
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# Deprecated model shortcuts, only used in errors and warnings
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OLD_MODEL_SHORTCUTS = {
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"en": "en_core_web_sm", "de": "de_core_news_sm", "es": "es_core_news_sm",
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"pt": "pt_core_news_sm", "fr": "fr_core_news_sm", "it": "it_core_news_sm",
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"nl": "nl_core_news_sm", "el": "el_core_news_sm", "nb": "nb_core_news_sm",
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"lt": "lt_core_news_sm", "xx": "xx_ent_wiki_sm"
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}
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# fmt: on
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@ -40,7 +40,7 @@ except ImportError:
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from .symbols import ORTH
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from .compat import cupy, CudaStream, is_windows, importlib_metadata
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from .errors import Errors, Warnings, OLD_MODEL_SHORTCUTS
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from .errors import Errors, Warnings
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from . import about
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if TYPE_CHECKING:
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@ -427,8 +427,6 @@ def load_model(
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return load_model_from_path(Path(name), **kwargs) # type: ignore[arg-type]
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elif hasattr(name, "exists"): # Path or Path-like to model data
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return load_model_from_path(name, **kwargs) # type: ignore[arg-type]
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if name in OLD_MODEL_SHORTCUTS:
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raise IOError(Errors.E941.format(name=name, full=OLD_MODEL_SHORTCUTS[name])) # type: ignore[index]
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raise IOError(Errors.E050.format(name=name))
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@ -51,7 +51,7 @@ markup is correct.
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"import spacy",
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"import package_name",
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"",
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"nlp = spacy.load('en')",
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"nlp = spacy.load('en_core_web_sm')",
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"nlp.add_pipe(package_name)"
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],
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"code_language": "python",
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@ -342,22 +342,6 @@ The easiest way to download a trained pipeline is via spaCy's
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[`download`](/api/cli#download) command. It takes care of finding the
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best-matching package compatible with your spaCy installation.
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> #### Important note for v3.0
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>
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> Note that as of spaCy v3.0, shortcut links like `en` that create (potentially
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> brittle) symlinks in your spaCy installation are **deprecated**. To download
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> and load an installed pipeline package, use its full name:
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>
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> ```diff
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> - python -m spacy download en
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> + python -m spacy download en_core_web_sm
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> ```
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>
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> ```diff
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> - nlp = spacy.load("en")
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> + nlp = spacy.load("en_core_web_sm")
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> ```
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```cli
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# Download best-matching version of a package for your spaCy installation
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$ python -m spacy download en_core_web_sm
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@ -489,17 +473,6 @@ spacy.cli.download("en_core_web_sm")
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To load a pipeline package, use [`spacy.load`](/api/top-level#spacy.load) with
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the package name or a path to the data directory:
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> #### Important note for v3.0
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>
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> Note that as of spaCy v3.0, shortcut links like `en` that create (potentially
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> brittle) symlinks in your spaCy installation are **deprecated**. To download
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> and load an installed pipeline package, use its full name:
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>
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> ```diff
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> - python -m spacy download en
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> + python -m spacy download en_core_web_sm
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> ```
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```python
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import spacy
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nlp = spacy.load("en_core_web_sm") # load package "en_core_web_sm"
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@ -1021,7 +1021,8 @@
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"author_links": {
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"github": "mholtzscher"
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},
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"category": ["pipeline"]
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"category": ["pipeline"],
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"spacy_version": 2
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},
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{
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"id": "spacy-sentence-segmenter",
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@ -1045,7 +1046,7 @@
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{
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"id": "spacy_cld",
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"title": "spaCy-CLD",
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"slogan": "Add language detection to your spaCy pipeline using CLD2",
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"slogan": "Add language detection to your spaCy v2 pipeline using CLD2",
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"description": "spaCy-CLD operates on `Doc` and `Span` spaCy objects. When called on a `Doc` or `Span`, the object is given two attributes: `languages` (a list of up to 3 language codes) and `language_scores` (a dictionary mapping language codes to confidence scores between 0 and 1).\n\nspacy-cld is a little extension that wraps the [PYCLD2](https://github.com/aboSamoor/pycld2) Python library, which in turn wraps the [Compact Language Detector 2](https://github.com/CLD2Owners/cld2) C library originally built at Google for the Chromium project. CLD2 uses character n-grams as features and a Naive Bayes classifier to identify 80+ languages from Unicode text strings (or XML/HTML). It can detect up to 3 different languages in a given document, and reports a confidence score (reported in with each language.",
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"github": "nickdavidhaynes/spacy-cld",
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"pip": "spacy_cld",
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@ -1065,7 +1066,8 @@
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"author_links": {
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"github": "nickdavidhaynes"
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},
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"category": ["pipeline"]
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"category": ["pipeline"],
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"spacy_version": 2
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},
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{
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"id": "spacy-iwnlp",
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@ -1139,7 +1141,8 @@
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"github": "sammous"
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},
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"category": ["pipeline"],
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"tags": ["pos", "lemmatizer", "french"]
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"tags": ["pos", "lemmatizer", "french"],
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"spacy_version": 2
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},
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{
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"id": "lemmy",
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@ -1333,8 +1336,8 @@
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},
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{
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"id": "neuralcoref",
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"slogan": "State-of-the-art coreference resolution based on neural nets and spaCy",
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"description": "This coreference resolution module is based on the super fast [spaCy](https://spacy.io/) parser and uses the neural net scoring model described in [Deep Reinforcement Learning for Mention-Ranking Coreference Models](http://cs.stanford.edu/people/kevclark/resources/clark-manning-emnlp2016-deep.pdf) by Kevin Clark and Christopher D. Manning, EMNLP 2016. Since ✨Neuralcoref v2.0, you can train the coreference resolution system on your own dataset — e.g., another language than English! — **provided you have an annotated dataset**. Note that to use neuralcoref with spaCy > 2.1.0, you'll have to install neuralcoref from source.",
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"slogan": "State-of-the-art coreference resolution based on neural nets and spaCy v2",
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"description": "This coreference resolution module is based on the super fast spaCy parser and uses the neural net scoring model described in [Deep Reinforcement Learning for Mention-Ranking Coreference Models](http://cs.stanford.edu/people/kevclark/resources/clark-manning-emnlp2016-deep.pdf) by Kevin Clark and Christopher D. Manning, EMNLP 2016. Since ✨Neuralcoref v2.0, you can train the coreference resolution system on your own dataset — e.g., another language than English! — **provided you have an annotated dataset**. Note that to use neuralcoref with spaCy > 2.1.0, you'll have to install neuralcoref from source, and v3+ is not supported.",
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"github": "huggingface/neuralcoref",
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"thumb": "https://i.imgur.com/j6FO9O6.jpg",
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"code_example": [
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@ -1355,7 +1358,8 @@
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"github": "huggingface"
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},
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"category": ["standalone", "conversational", "models"],
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"tags": ["coref"]
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"tags": ["coref"],
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"spacy_version": 2
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},
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{
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"id": "neuralcoref-vizualizer",
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@ -1431,7 +1435,7 @@
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"import spacy",
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"import explacy",
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"",
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"nlp = spacy.load('en')",
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"nlp = spacy.load('en_core_web_sm')",
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"explacy.print_parse_info(nlp, 'The salad was surprisingly tasty.')"
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],
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"author": "Tyler Neylon",
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