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Fix dropout in tensorizer, update comment

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This commit is contained in:
Matthew Honnibal 2018-11-03 12:46:58 +00:00
parent 0127f10ba3
commit ad44982f01
1 changed files with 3 additions and 3 deletions
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6
spacy/pipeline.pyx
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@ -430,7 +430,7 @@ def _load_cfg(path):
class Tensorizer(Pipe): class Tensorizer(Pipe):
"""Assign position-sensitive vectors to tokens, using a CNN or RNN.""" """Pre-train position-sensitive vectors for tokens."""
name = 'tensorizer' name = 'tensorizer'
@classmethod @classmethod
@ -443,7 +443,7 @@ class Tensorizer(Pipe):
RETURNS (Model): A `thinc.neural.Model` or similar instance. RETURNS (Model): A `thinc.neural.Model` or similar instance.
""" """
input_size = util.env_opt('token_vector_width', cfg.get('input_size', 128)) input_size = util.env_opt('token_vector_width', cfg.get('input_size', 128))
return zero_init(Affine(output_size, input_size)) return zero_init(Affine(output_size, input_size, drop_factor=0.0))
def __init__(self, vocab, model=True, **cfg): def __init__(self, vocab, model=True, **cfg):
"""Construct a new statistical model. Weights are not allocated on """Construct a new statistical model. Weights are not allocated on
@ -1119,7 +1119,7 @@ class TextCategorizer(Pipe):
d_scores = (scores-truths) / scores.shape[0] d_scores = (scores-truths) / scores.shape[0]
d_scores *= not_missing d_scores *= not_missing
mean_square_error = ((scores-truths)**2).sum(axis=1).mean() mean_square_error = ((scores-truths)**2).sum(axis=1).mean()
return mean_square_error, d_scores return float(mean_square_error), d_scores
def add_label(self, label): def add_label(self, label):
if label in self.labels: if label in self.labels: