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606273f7e4
* Normalize whitespace in evaluate CLI output test Depending on terminal settings, lines may be padded to the screen width so the comparison is too strict with only the command string replacement. * Move to test util method * Change to normalization method
103 lines
3.2 KiB
Python
103 lines
3.2 KiB
Python
import numpy
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import tempfile
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import contextlib
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import re
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import srsly
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from spacy.tokens import Doc
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from spacy.vocab import Vocab
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from spacy.util import make_tempdir # noqa: F401
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from spacy.training import split_bilu_label
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from thinc.api import get_current_ops
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@contextlib.contextmanager
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def make_tempfile(mode="r"):
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f = tempfile.TemporaryFile(mode=mode)
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yield f
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f.close()
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def get_batch(batch_size):
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vocab = Vocab()
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docs = []
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start = 0
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for size in range(1, batch_size + 1):
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# Make the words numbers, so that they're distinct
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# across the batch, and easy to track.
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numbers = [str(i) for i in range(start, start + size)]
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docs.append(Doc(vocab, words=numbers))
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start += size
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return docs
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def get_random_doc(n_words):
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vocab = Vocab()
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# Make the words numbers, so that they're easy to track.
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numbers = [str(i) for i in range(0, n_words)]
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return Doc(vocab, words=numbers)
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def apply_transition_sequence(parser, doc, sequence):
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"""Perform a series of pre-specified transitions, to put the parser in a
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desired state."""
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for action_name in sequence:
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if "-" in action_name:
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move, label = split_bilu_label(action_name)
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parser.add_label(label)
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with parser.step_through(doc) as stepwise:
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for transition in sequence:
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stepwise.transition(transition)
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def add_vecs_to_vocab(vocab, vectors):
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"""Add list of vector tuples to given vocab. All vectors need to have the
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same length. Format: [("text", [1, 2, 3])]"""
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length = len(vectors[0][1])
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vocab.reset_vectors(width=length)
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for word, vec in vectors:
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vocab.set_vector(word, vector=vec)
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return vocab
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def get_cosine(vec1, vec2):
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"""Get cosine for two given vectors"""
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OPS = get_current_ops()
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v1 = OPS.to_numpy(OPS.asarray(vec1))
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v2 = OPS.to_numpy(OPS.asarray(vec2))
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return numpy.dot(v1, v2) / (numpy.linalg.norm(v1) * numpy.linalg.norm(v2))
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def assert_docs_equal(doc1, doc2):
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"""Compare two Doc objects and assert that they're equal. Tests for tokens,
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tags, dependencies and entities."""
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assert [t.orth for t in doc1] == [t.orth for t in doc2]
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assert [t.pos for t in doc1] == [t.pos for t in doc2]
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assert [t.tag for t in doc1] == [t.tag for t in doc2]
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assert [t.head.i for t in doc1] == [t.head.i for t in doc2]
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assert [t.dep for t in doc1] == [t.dep for t in doc2]
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assert [t.is_sent_start for t in doc1] == [t.is_sent_start for t in doc2]
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assert [t.ent_type for t in doc1] == [t.ent_type for t in doc2]
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assert [t.ent_iob for t in doc1] == [t.ent_iob for t in doc2]
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for ent1, ent2 in zip(doc1.ents, doc2.ents):
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assert ent1.start == ent2.start
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assert ent1.end == ent2.end
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assert ent1.label == ent2.label
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assert ent1.kb_id == ent2.kb_id
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def assert_packed_msg_equal(b1, b2):
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"""Assert that two packed msgpack messages are equal."""
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msg1 = srsly.msgpack_loads(b1)
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msg2 = srsly.msgpack_loads(b2)
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assert sorted(msg1.keys()) == sorted(msg2.keys())
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for (k1, v1), (k2, v2) in zip(sorted(msg1.items()), sorted(msg2.items())):
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assert k1 == k2
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assert v1 == v2
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def normalize_whitespace(s):
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return re.sub(r"\s+", " ", s)
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