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Update tests

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This commit is contained in:
Matthew Honnibal 2020-07-29 13:47:37 +02:00
parent 07b47eaac8
commit f0cf4a2dca
2 changed files with 17 additions and 16 deletions
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4
spacy/tests/serialize/test_serialize_config.py
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@ -41,7 +41,7 @@ factory = "tagger"
@architectures = "spacy.Tagger.v1"
[components.tagger.model.tok2vec]
@architectures = "spacy.Tok2VecTensors.v1"
@architectures = "spacy.Tok2VecListener.v1"
width = ${components.tok2vec.model:width}
"""
@ -71,7 +71,7 @@ def my_parser():
tok2vec = build_Tok2Vec_model(
MultiHashEmbed(
width=321,
embed_size=5432,
rows=5432,
also_embed_subwords=True,
also_use_static_vectors=False
),

29
spacy/tests/test_tok2vec.py
View File

@ -1,7 +1,8 @@
import pytest
from spacy.ml.models.tok2vec import build_Tok2Vec_model
from spacy.ml.models.tok2vec import MultiHashEmbed, MaxoutWindowEncoder
from spacy.ml.models.tok2vec import MultiHashEmbed, CharacterEmbed
from spacy.ml.models.tok2vec import MishWindowEncoder, MaxoutWindowEncoder
from spacy.vocab import Vocab
from spacy.tokens import Doc
@ -60,26 +61,26 @@ def test_tok2vec_batch_sizes(batch_size, width, embed_size):
# fmt: off
@pytest.mark.xfail(reason="TODO: Update for new signature")
@pytest.mark.parametrize(
"tok2vec_config",
"width,embed_arch,embed_config,encode_arch,encode_config",
[
{"width": 8, "embed_size": 100, "char_embed": False, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 1, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": True, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": True, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 1, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": True, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": False, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 1, "conv_depth": 6, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": True, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": False, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 1, "conv_depth": 6, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": True, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": False, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 1, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": False, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": False, "nM": 64, "nC": 8, "pretrained_vectors": None, "window_size": 3, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": False, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": True, "nM": 81, "nC": 8, "pretrained_vectors": None, "window_size": 3, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": False, "dropout": None},
{"width": 8, "embed_size": 100, "char_embed": True, "nM": 81, "nC": 9, "pretrained_vectors": None, "window_size": 3, "conv_depth": 2, "bilstm_depth": 0, "maxout_pieces": 3, "subword_features": False, "dropout": None},
(8, MultiHashEmbed, {"rows": 100, "also_embed_subwords": True, "also_use_static_vectors": False}, MaxoutWindowEncoder, {"window_size": 1, "maxout_pieces": 3, "depth": 2}),
(8, MultiHashEmbed, {"rows": 100, "also_embed_subwords": True, "also_use_static_vectors": False}, MishWindowEncoder, {"window_size": 1, "depth": 6}),
(8, CharacterEmbed, {"rows": 100, "nM": 64, "nC": 8}, MaxoutWindowEncoder, {"window_size": 1, "maxout_pieces": 3, "depth": 3}),
(8, CharacterEmbed, {"rows": 100, "nM": 16, "nC": 2}, MishWindowEncoder, {"window_size": 1, "depth": 3}),
],
)
# fmt: on
def test_tok2vec_configs(tok2vec_config):
def test_tok2vec_configs(width, embed_arch, embed_config, encode_arch, encode_config):
embed_config["width"] = width
encode_config["width"] = width
docs = get_batch(3)
tok2vec = build_Tok2Vec_model_from_old_args(**tok2vec_config)
tok2vec = build_Tok2Vec_model(
embed_arch(**embed_config),
encode_arch(**encode_config)
)
tok2vec.initialize(docs)
vectors, backprop = tok2vec.begin_update(docs)
assert len(vectors) == len(docs)
assert vectors[0].shape == (len(docs[0]), tok2vec_config["width"])
assert vectors[0].shape == (len(docs[0]), width)
backprop(vectors)