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## Description Related issues: #2379 (should be fixed by separating model tests) * **total execution time down from > 300 seconds to under 60 seconds** 🎉 * removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure * changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version) * merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways) * tidied up and rewrote existing tests wherever possible ### Todo - [ ] move tests to `/tests` and adjust CI commands accordingly - [x] move model test suite from internal repo to `spacy-models` - [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~ - [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted - [ ] update documentation on how to run tests ### Types of change enhancement, tests ## 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. - [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
191 lines
6.1 KiB
Python
191 lines
6.1 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.attrs import IS_ALPHA, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_TITLE, IS_STOP
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from spacy.symbols import VERB
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from spacy.vocab import Vocab
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from spacy.tokens import Doc
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from ..util import get_doc
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@pytest.fixture
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def doc(en_tokenizer):
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text = "This is a sentence. This is another sentence. And a third."
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heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3, 0, 1, -2, -1]
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deps = ['nsubj', 'ROOT', 'det', 'attr', 'punct', 'nsubj', 'ROOT', 'det',
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'attr', 'punct', 'ROOT', 'det', 'npadvmod', 'punct']
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tokens = en_tokenizer(text)
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return get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
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def test_doc_token_api_strings(en_tokenizer):
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text = "Give it back! He pleaded."
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pos = ['VERB', 'PRON', 'PART', 'PUNCT', 'PRON', 'VERB', 'PUNCT']
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heads = [0, -1, -2, -3, 1, 0, -1]
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deps = ['ROOT', 'dobj', 'prt', 'punct', 'nsubj', 'ROOT', 'punct']
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps)
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assert doc[0].orth_ == 'Give'
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assert doc[0].text == 'Give'
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assert doc[0].text_with_ws == 'Give '
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assert doc[0].lower_ == 'give'
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assert doc[0].shape_ == 'Xxxx'
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assert doc[0].prefix_ == 'G'
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assert doc[0].suffix_ == 'ive'
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assert doc[0].pos_ == 'VERB'
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assert doc[0].dep_ == 'ROOT'
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def test_doc_token_api_flags(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].check_flag(IS_ALPHA)
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assert not tokens[0].check_flag(IS_DIGIT)
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assert tokens[0].check_flag(IS_TITLE)
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assert tokens[1].check_flag(IS_LOWER)
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assert tokens[3].check_flag(IS_PUNCT)
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assert tokens[2].check_flag(IS_STOP)
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assert not tokens[5].check_flag(IS_STOP)
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# TODO: Test more of these, esp. if a bug is found
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@pytest.mark.parametrize('text', ["Give it back! He pleaded."])
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def test_doc_token_api_prob_inherited_from_vocab(en_tokenizer, text):
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word = text.split()[0]
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en_tokenizer.vocab[word].prob = -1
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tokens = en_tokenizer(text)
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assert tokens[0].prob != 0
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@pytest.mark.parametrize('text', ["one two"])
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def test_doc_token_api_str_builtin(en_tokenizer, text):
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tokens = en_tokenizer(text)
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assert str(tokens[0]) == text.split(' ')[0]
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assert str(tokens[1]) == text.split(' ')[1]
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def test_doc_token_api_is_properties(en_vocab):
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doc = Doc(en_vocab, words=["Hi", ",", "my", "email", "is", "test@me.com"])
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assert doc[0].is_title
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assert doc[0].is_alpha
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assert not doc[0].is_digit
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assert doc[1].is_punct
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assert doc[3].is_ascii
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assert not doc[3].like_url
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assert doc[4].is_lower
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assert doc[5].like_email
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def test_doc_token_api_vectors():
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vocab = Vocab()
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vocab.reset_vectors(width=2)
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vocab.set_vector('apples', vector=numpy.asarray([0., 2.], dtype='f'))
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vocab.set_vector('oranges', vector=numpy.asarray([0., 1.], dtype='f'))
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doc = Doc(vocab, words=['apples', 'oranges', 'oov'])
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assert doc.has_vector
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assert doc[0].has_vector
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assert doc[1].has_vector
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assert not doc[2].has_vector
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apples_norm = (0*0 + 2*2) ** 0.5
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oranges_norm = (0*0 + 1*1) ** 0.5
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cosine = ((0*0) + (2*1)) / (apples_norm * oranges_norm)
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assert doc[0].similarity(doc[1]) == cosine
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def test_doc_token_api_ancestors(en_tokenizer):
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# the structure of this sentence depends on the English annotation scheme
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text = "Yesterday I saw a dog that barked loudly."
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heads = [2, 1, 0, 1, -2, 1, -2, -1, -6]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
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assert [t.text for t in doc[6].ancestors] == ["dog", "saw"]
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assert [t.text for t in doc[1].ancestors] == ["saw"]
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assert [t.text for t in doc[2].ancestors] == []
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assert doc[2].is_ancestor(doc[7])
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assert not doc[6].is_ancestor(doc[2])
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def test_doc_token_api_head_setter(en_tokenizer):
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# the structure of this sentence depends on the English annotation scheme
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text = "Yesterday I saw a dog that barked loudly."
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heads = [2, 1, 0, 1, -2, 1, -2, -1, -6]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
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assert doc[6].n_lefts == 1
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assert doc[6].n_rights == 1
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assert doc[6].left_edge.i == 5
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assert doc[6].right_edge.i == 7
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assert doc[4].n_lefts == 1
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assert doc[4].n_rights == 1
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assert doc[4].left_edge.i == 3
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assert doc[4].right_edge.i == 7
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assert doc[3].n_lefts == 0
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assert doc[3].n_rights == 0
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assert doc[3].left_edge.i == 3
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assert doc[3].right_edge.i == 3
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assert doc[2].left_edge.i == 0
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assert doc[2].right_edge.i == 8
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doc[6].head = doc[3]
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assert doc[6].n_lefts == 1
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assert doc[6].n_rights == 1
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assert doc[6].left_edge.i == 5
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assert doc[6].right_edge.i == 7
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assert doc[3].n_lefts == 0
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assert doc[3].n_rights == 1
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assert doc[3].left_edge.i == 3
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assert doc[3].right_edge.i == 7
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assert doc[4].n_lefts == 1
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assert doc[4].n_rights == 0
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assert doc[4].left_edge.i == 3
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assert doc[4].right_edge.i == 7
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assert doc[2].left_edge.i == 0
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assert doc[2].right_edge.i == 8
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doc[0].head = doc[5]
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assert doc[5].left_edge.i == 0
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assert doc[6].left_edge.i == 0
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assert doc[3].left_edge.i == 0
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assert doc[4].left_edge.i == 0
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assert doc[2].left_edge.i == 0
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def test_is_sent_start(en_tokenizer):
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doc = en_tokenizer('This is a sentence. This is another.')
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assert doc[5].is_sent_start is None
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doc[5].is_sent_start = True
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assert doc[5].is_sent_start is True
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doc.is_parsed = True
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assert len(list(doc.sents)) == 2
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def test_set_pos():
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doc = Doc(Vocab(), words=['hello', 'world'])
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doc[0].pos_ = 'NOUN'
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assert doc[0].pos_ == 'NOUN'
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doc[1].pos = VERB
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assert doc[1].pos_ == 'VERB'
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def test_tokens_sent(doc):
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"""Test token.sent property"""
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assert len(list(doc.sents)) == 3
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assert doc[1].sent.text == 'This is a sentence .'
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assert doc[7].sent.text == 'This is another sentence .'
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assert doc[1].sent.root.left_edge.text == 'This'
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assert doc[7].sent.root.left_edge.text == 'This'
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