mirror of https://github.com/explosion/spaCy.git
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
import pytest
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from spacy.gold import Example
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from .util import get_random_doc
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from spacy.util import minibatch_by_words
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@pytest.mark.parametrize(
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"doc_sizes, expected_batches",
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[
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([400, 400, 199], [3]),
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([400, 400, 199, 3], [4]),
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([400, 400, 199, 3, 200], [3, 2]),
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([400, 400, 199, 3, 1], [5]),
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([400, 400, 199, 3, 1, 1500], [5]), # 1500 will be discarded
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([400, 400, 199, 3, 1, 200], [3, 3]),
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([400, 400, 199, 3, 1, 999], [3, 3]),
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([400, 400, 199, 3, 1, 999, 999], [3, 2, 1, 1]),
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([1, 2, 999], [3]),
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([1, 2, 999, 1], [4]),
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([1, 200, 999, 1], [2, 2]),
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([1, 999, 200, 1], [2, 2]),
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],
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)
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def test_util_minibatch(doc_sizes, expected_batches):
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docs = [get_random_doc(doc_size) for doc_size in doc_sizes]
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examples = [Example(doc=doc) for doc in docs]
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tol = 0.2
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batch_size = 1000
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batches = list(
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minibatch_by_words(
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examples=examples, size=batch_size, tolerance=tol, discard_oversize=True
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)
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)
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assert [len(batch) for batch in batches] == expected_batches
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max_size = batch_size + batch_size * tol
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for batch in batches:
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assert sum([len(example.doc) for example in batch]) < max_size
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@pytest.mark.parametrize(
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"doc_sizes, expected_batches",
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[
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([400, 4000, 199], [1, 2]),
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([400, 400, 199, 3000, 200], [1, 4]),
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([400, 400, 199, 3, 1, 1500], [1, 5]),
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([400, 400, 199, 3000, 2000, 200, 200], [1, 1, 3, 2]),
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([1, 2, 9999], [1, 2]),
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([2000, 1, 2000, 1, 1, 1, 2000], [1, 1, 1, 4]),
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],
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)
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def test_util_minibatch_oversize(doc_sizes, expected_batches):
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""" Test that oversized documents are returned in their own batch"""
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docs = [get_random_doc(doc_size) for doc_size in doc_sizes]
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examples = [Example(doc=doc) for doc in docs]
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tol = 0.2
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batch_size = 1000
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batches = list(
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minibatch_by_words(
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examples=examples, size=batch_size, tolerance=tol, discard_oversize=False
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)
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)
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assert [len(batch) for batch in batches] == expected_batches
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