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
360 lines
11 KiB
Python
360 lines
11 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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import numpy
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from spacy.tokens import Doc
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from spacy.vocab import Vocab
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from spacy.attrs import LEMMA
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from ..util import get_doc
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@pytest.mark.parametrize("text", [["one", "two", "three"]])
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def test_doc_api_compare_by_string_position(en_vocab, text):
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doc = Doc(en_vocab, words=text)
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# Get the tokens in this order, so their ID ordering doesn't match the idx
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token3 = doc[-1]
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token2 = doc[-2]
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token1 = doc[-1]
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token1, token2, token3 = doc
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assert token1 < token2 < token3
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assert not token1 > token2
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assert token2 > token1
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assert token2 <= token3
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assert token3 >= token1
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def test_doc_api_getitem(en_tokenizer):
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text = "Give it back! He pleaded."
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tokens = en_tokenizer(text)
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assert tokens[0].text == "Give"
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assert tokens[-1].text == "."
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with pytest.raises(IndexError):
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tokens[len(tokens)]
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def to_str(span):
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return "/".join(token.text for token in span)
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span = tokens[1:1]
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assert not to_str(span)
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span = tokens[1:4]
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assert to_str(span) == "it/back/!"
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span = tokens[1:4:1]
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assert to_str(span) == "it/back/!"
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with pytest.raises(ValueError):
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tokens[1:4:2]
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with pytest.raises(ValueError):
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tokens[1:4:-1]
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span = tokens[-3:6]
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assert to_str(span) == "He/pleaded"
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span = tokens[4:-1]
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assert to_str(span) == "He/pleaded"
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span = tokens[-5:-3]
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assert to_str(span) == "back/!"
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span = tokens[5:4]
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assert span.start == span.end == 5 and not to_str(span)
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span = tokens[4:-3]
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assert span.start == span.end == 4 and not to_str(span)
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span = tokens[:]
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assert to_str(span) == "Give/it/back/!/He/pleaded/."
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span = tokens[4:]
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assert to_str(span) == "He/pleaded/."
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span = tokens[:4]
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assert to_str(span) == "Give/it/back/!"
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span = tokens[:-3]
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assert to_str(span) == "Give/it/back/!"
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span = tokens[-3:]
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assert to_str(span) == "He/pleaded/."
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span = tokens[4:50]
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assert to_str(span) == "He/pleaded/."
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span = tokens[-50:4]
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assert to_str(span) == "Give/it/back/!"
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span = tokens[-50:-40]
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assert span.start == span.end == 0 and not to_str(span)
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span = tokens[40:50]
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assert span.start == span.end == 7 and not to_str(span)
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span = tokens[1:4]
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assert span[0].orth_ == "it"
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subspan = span[:]
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assert to_str(subspan) == "it/back/!"
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subspan = span[:2]
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assert to_str(subspan) == "it/back"
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subspan = span[1:]
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assert to_str(subspan) == "back/!"
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subspan = span[:-1]
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assert to_str(subspan) == "it/back"
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subspan = span[-2:]
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assert to_str(subspan) == "back/!"
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subspan = span[1:2]
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assert to_str(subspan) == "back"
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subspan = span[-2:-1]
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assert to_str(subspan) == "back"
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subspan = span[-50:50]
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assert to_str(subspan) == "it/back/!"
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subspan = span[50:-50]
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assert subspan.start == subspan.end == 4 and not to_str(subspan)
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@pytest.mark.parametrize(
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"text", ["Give it back! He pleaded.", " Give it back! He pleaded. "]
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)
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def test_doc_api_serialize(en_tokenizer, text):
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tokens = en_tokenizer(text)
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new_tokens = Doc(tokens.vocab).from_bytes(tokens.to_bytes())
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assert tokens.text == new_tokens.text
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assert [t.text for t in tokens] == [t.text for t in new_tokens]
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assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
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new_tokens = Doc(tokens.vocab).from_bytes(
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tokens.to_bytes(tensor=False), tensor=False
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)
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assert tokens.text == new_tokens.text
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assert [t.text for t in tokens] == [t.text for t in new_tokens]
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assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
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new_tokens = Doc(tokens.vocab).from_bytes(
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tokens.to_bytes(sentiment=False), sentiment=False
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)
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assert tokens.text == new_tokens.text
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assert [t.text for t in tokens] == [t.text for t in new_tokens]
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assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
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def test_doc_api_set_ents(en_tokenizer):
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text = "I use goggle chrone to surf the web"
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tokens = en_tokenizer(text)
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assert len(tokens.ents) == 0
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tokens.ents = [(tokens.vocab.strings["PRODUCT"], 2, 4)]
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assert len(list(tokens.ents)) == 1
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assert [t.ent_iob for t in tokens] == [0, 0, 3, 1, 0, 0, 0, 0]
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assert tokens.ents[0].label_ == "PRODUCT"
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assert tokens.ents[0].start == 2
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assert tokens.ents[0].end == 4
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def test_doc_api_merge(en_tokenizer):
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text = "WKRO played songs by the beach boys all night"
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# merge 'The Beach Boys'
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doc = en_tokenizer(text)
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assert len(doc) == 9
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doc.merge(
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doc[4].idx,
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doc[6].idx + len(doc[6]),
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tag="NAMED",
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lemma="LEMMA",
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ent_type="TYPE",
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)
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assert len(doc) == 7
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assert doc[4].text == "the beach boys"
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assert doc[4].text_with_ws == "the beach boys "
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assert doc[4].tag_ == "NAMED"
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# merge 'all night'
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doc = en_tokenizer(text)
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assert len(doc) == 9
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doc.merge(
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doc[7].idx,
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doc[8].idx + len(doc[8]),
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tag="NAMED",
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lemma="LEMMA",
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ent_type="TYPE",
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)
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assert len(doc) == 8
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assert doc[7].text == "all night"
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assert doc[7].text_with_ws == "all night"
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# merge both with bulk merge
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doc = en_tokenizer(text)
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assert len(doc) == 9
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with doc.retokenize() as retokenizer:
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retokenizer.merge(doc[4: 7], attrs={'tag':'NAMED', 'lemma':'LEMMA',
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'ent_type':'TYPE'})
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retokenizer.merge(doc[7: 9], attrs={'tag':'NAMED', 'lemma':'LEMMA',
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'ent_type':'TYPE'})
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assert len(doc) == 6
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assert doc[4].text == 'the beach boys'
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assert doc[4].text_with_ws == 'the beach boys '
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assert doc[4].tag_ == 'NAMED'
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assert doc[5].text == 'all night'
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assert doc[5].text_with_ws == 'all night'
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assert doc[5].tag_ == 'NAMED'
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def test_doc_api_merge_children(en_tokenizer):
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"""Test that attachments work correctly after merging."""
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text = "WKRO played songs by the beach boys all night"
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doc = en_tokenizer(text)
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assert len(doc) == 9
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doc.merge(
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doc[4].idx,
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doc[6].idx + len(doc[6]),
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tag="NAMED",
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lemma="LEMMA",
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ent_type="TYPE",
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)
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for word in doc:
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if word.i < word.head.i:
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assert word in list(word.head.lefts)
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elif word.i > word.head.i:
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assert word in list(word.head.rights)
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def test_doc_api_merge_hang(en_tokenizer):
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text = "through North and South Carolina"
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doc = en_tokenizer(text)
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doc.merge(18, 32, tag="", lemma="", ent_type="ORG")
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doc.merge(8, 32, tag="", lemma="", ent_type="ORG")
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def test_doc_api_retokenizer(en_tokenizer):
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doc = en_tokenizer("WKRO played songs by the beach boys all night")
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with doc.retokenize() as retokenizer:
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retokenizer.merge(doc[4:7])
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assert len(doc) == 7
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assert doc[4].text == "the beach boys"
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def test_doc_api_retokenizer_attrs(en_tokenizer):
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doc = en_tokenizer("WKRO played songs by the beach boys all night")
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# test both string and integer attributes and values
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attrs = {LEMMA: "boys", "ENT_TYPE": doc.vocab.strings["ORG"]}
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with doc.retokenize() as retokenizer:
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retokenizer.merge(doc[4:7], attrs=attrs)
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assert len(doc) == 7
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assert doc[4].text == "the beach boys"
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assert doc[4].lemma_ == "boys"
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assert doc[4].ent_type_ == "ORG"
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@pytest.mark.xfail
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def test_doc_api_retokenizer_lex_attrs(en_tokenizer):
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"""Test that lexical attributes can be changed (see #2390)."""
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doc = en_tokenizer("WKRO played beach boys songs")
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assert not any(token.is_stop for token in doc)
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with doc.retokenize() as retokenizer:
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retokenizer.merge(doc[2:4], attrs={"LEMMA": "boys", "IS_STOP": True})
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assert doc[2].text == "beach boys"
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assert doc[2].lemma_ == "boys"
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assert doc[2].is_stop
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new_doc = Doc(doc.vocab, words=["beach boys"])
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assert new_doc[0].is_stop
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def test_doc_api_sents_empty_string(en_tokenizer):
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doc = en_tokenizer("")
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doc.is_parsed = True
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sents = list(doc.sents)
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assert len(sents) == 0
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|
|
|
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def test_doc_api_runtime_error(en_tokenizer):
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# Example that caused run-time error while parsing Reddit
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# fmt: off
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text = "67% of black households are single parent \n\n72% of all black babies born out of wedlock \n\n50% of all black kids don\u2019t finish high school"
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deps = ["nsubj", "prep", "amod", "pobj", "ROOT", "amod", "attr", "",
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"nummod", "prep", "det", "amod", "pobj", "acl", "prep", "prep",
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|
"pobj", "", "nummod", "prep", "det", "amod", "pobj", "aux", "neg",
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|
"ROOT", "amod", "dobj"]
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|
# fmt: on
|
|
|
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], deps=deps)
|
|
|
|
nps = []
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|
for np in doc.noun_chunks:
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|
while len(np) > 1 and np[0].dep_ not in ("advmod", "amod", "compound"):
|
|
np = np[1:]
|
|
if len(np) > 1:
|
|
nps.append(
|
|
(np.start_char, np.end_char, np.root.tag_, np.text, np.root.ent_type_)
|
|
)
|
|
for np in nps:
|
|
start, end, tag, lemma, ent_type = np
|
|
doc.merge(start, end, tag=tag, lemma=lemma, ent_type=ent_type)
|
|
|
|
|
|
def test_doc_api_right_edge(en_tokenizer):
|
|
"""Test for bug occurring from Unshift action, causing incorrect right edge"""
|
|
# fmt: off
|
|
text = "I have proposed to myself, for the sake of such as live under the government of the Romans, to translate those books into the Greek tongue."
|
|
heads = [2, 1, 0, -1, -1, -3, 15, 1, -2, -1, 1, -3, -1, -1, 1, -2, -1, 1,
|
|
-2, -7, 1, -19, 1, -2, -3, 2, 1, -3, -26]
|
|
# fmt: on
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
|
|
assert doc[6].text == "for"
|
|
subtree = [w.text for w in doc[6].subtree]
|
|
assert subtree == [
|
|
"for",
|
|
"the",
|
|
"sake",
|
|
"of",
|
|
"such",
|
|
"as",
|
|
"live",
|
|
"under",
|
|
"the",
|
|
"government",
|
|
"of",
|
|
"the",
|
|
"Romans",
|
|
",",
|
|
]
|
|
assert doc[6].right_edge.text == ","
|
|
|
|
|
|
def test_doc_api_has_vector():
|
|
vocab = Vocab()
|
|
vocab.reset_vectors(width=2)
|
|
vocab.set_vector("kitten", vector=numpy.asarray([0.0, 2.0], dtype="f"))
|
|
doc = Doc(vocab, words=["kitten"])
|
|
assert doc.has_vector
|
|
|
|
|
|
def test_doc_api_similarity_match():
|
|
doc = Doc(Vocab(), words=["a"])
|
|
with pytest.warns(None):
|
|
assert doc.similarity(doc[0]) == 1.0
|
|
assert doc.similarity(doc.vocab["a"]) == 1.0
|
|
doc2 = Doc(doc.vocab, words=["a", "b", "c"])
|
|
with pytest.warns(None):
|
|
assert doc.similarity(doc2[:1]) == 1.0
|
|
assert doc.similarity(doc2) == 0.0
|
|
|
|
|
|
def test_lowest_common_ancestor(en_tokenizer):
|
|
tokens = en_tokenizer("the lazy dog slept")
|
|
doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[2, 1, 1, 0])
|
|
lca = doc.get_lca_matrix()
|
|
assert lca[1, 1] == 1
|
|
assert lca[0, 1] == 2
|
|
assert lca[1, 2] == 2
|
|
|
|
|
|
def test_parse_tree(en_tokenizer):
|
|
"""Tests doc.print_tree() method."""
|
|
text = "I like New York in Autumn."
|
|
heads = [1, 0, 1, -2, -3, -1, -5]
|
|
tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, tags=tags)
|
|
# full method parse_tree(text) is a trivial composition
|
|
trees = doc.print_tree()
|
|
assert len(trees) > 0
|
|
tree = trees[0]
|
|
assert all(
|
|
k in list(tree.keys())
|
|
for k in ["word", "lemma", "NE", "POS_fine", "POS_coarse", "arc", "modifiers"]
|
|
)
|
|
assert tree["word"] == "like" # check root is correct
|