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Example.get_aligned_parse: Handle unit and zero length vectors correctly (#11026)

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* `Example.get_aligned_parse`: Do not squeeze gold token idx vector
Correctly handle zero-size vectors passed to `np.vectorize`

* Add tests

* Use `Doc` ctor to initialize attributes

* Remove unintended change

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Remove unused import

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
This commit is contained in:
Madeesh Kannan 2022-06-28 19:42:58 +02:00 committed by GitHub
parent a9559e7435
commit 1d5cad0b42
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2 changed files with 28 additions and 3 deletions
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25
spacy/tests/training/test_training.py
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@ -679,6 +679,31 @@ def test_projectivize(en_tokenizer):
assert proj_heads == [3, 2, 3, 3, 3] assert proj_heads == [3, 2, 3, 3, 3]
assert nonproj_heads == [3, 2, 3, 3, 2] assert nonproj_heads == [3, 2, 3, 3, 2]
# Test single token documents
doc = en_tokenizer("Conrail")
heads = [0]
deps = ["dep"]
example = Example.from_dict(doc, {"heads": heads, "deps": deps})
proj_heads, proj_labels = example.get_aligned_parse(projectivize=True)
assert proj_heads == heads
assert proj_labels == deps
# Test documents with no alignments
doc_a = Doc(
doc.vocab, words=["Double-Jointed"], spaces=[False], deps=["ROOT"], heads=[0]
)
doc_b = Doc(
doc.vocab,
words=["Double", "-", "Jointed"],
spaces=[True, True, True],
deps=["amod", "punct", "ROOT"],
heads=[2, 2, 2],
)
example = Example(doc_a, doc_b)
proj_heads, proj_deps = example.get_aligned_parse(projectivize=True)
assert proj_heads == [None]
assert proj_deps == [None]
def test_iob_to_biluo(): def test_iob_to_biluo():
good_iob = ["O", "O", "B-LOC", "I-LOC", "O", "B-PERSON"] good_iob = ["O", "O", "B-LOC", "I-LOC", "O", "B-PERSON"]

6
spacy/training/example.pyx
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@ -249,9 +249,9 @@ cdef class Example:
# Fetch all aligned gold token incides. # Fetch all aligned gold token incides.
if c2g_single_toks.shape == cand_to_gold.lengths.shape: if c2g_single_toks.shape == cand_to_gold.lengths.shape:
# This the most likely case. # This the most likely case.
gold_i = cand_to_gold[:].squeeze() gold_i = cand_to_gold[:]
else: else:
gold_i = numpy.vectorize(lambda x: cand_to_gold[int(x)][0])(c2g_single_toks).squeeze() gold_i = numpy.vectorize(lambda x: cand_to_gold[int(x)][0], otypes='i')(c2g_single_toks)
# Fetch indices of all gold heads for the aligned gold tokens. # Fetch indices of all gold heads for the aligned gold tokens.
heads = numpy.asarray(heads, dtype='i') heads = numpy.asarray(heads, dtype='i')
@ -261,7 +261,7 @@ cdef class Example:
# gold tokens (and are aligned to a single candidate token). # gold tokens (and are aligned to a single candidate token).
g2c_len_heads = gold_to_cand.lengths[gold_head_i] g2c_len_heads = gold_to_cand.lengths[gold_head_i]
g2c_len_heads = numpy.where(g2c_len_heads == 1)[0] g2c_len_heads = numpy.where(g2c_len_heads == 1)[0]
g2c_i = numpy.vectorize(lambda x: gold_to_cand[int(x)][0])(gold_head_i[g2c_len_heads]).squeeze() g2c_i = numpy.vectorize(lambda x: gold_to_cand[int(x)][0], otypes='i')(gold_head_i[g2c_len_heads]).squeeze()
# Update head/dep alignments with the above. # Update head/dep alignments with the above.
aligned_heads = numpy.full((self.x.length), None) aligned_heads = numpy.full((self.x.length), None)