SUMIN/HuggingFace_transformer
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delete print and make style

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Patrick von Platen
2020-03-10 14:32:21 +01:00
parent ca1330f0b2
commit 9b8ee8cea0
1 changed files with 2 additions and 5 deletions
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7
src/transformers/modeling_tf_utils.py
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@@ -926,7 +926,7 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin):
if temperature != 1.0: if temperature != 1.0:
next_token_logits = next_token_logits / temperature next_token_logits = next_token_logits / temperature
# calculate log softmax score # calculate log softmax score
scores = tf.nn.log_softmax(next_token_logits, axis=-1) # (batch_size * num_beams, vocab_size) scores = tf.nn.log_softmax(next_token_logits, axis=-1) # (batch_size * num_beams, vocab_size)
# set eos token prob to zero if min_length is not reached # set eos token prob to zero if min_length is not reached
@@ -937,9 +937,7 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin):
) )
eos_token_indices_mask = tf.broadcast_to(is_token_logit_eos_token, [batch_size, vocab_size]) eos_token_indices_mask = tf.broadcast_to(is_token_logit_eos_token, [batch_size, vocab_size])
scores = set_tensor_by_indices_to_value( scores = set_tensor_by_indices_to_value(scores, eos_token_indices_mask, -float("inf"))
scores, eos_token_indices_mask, -float("inf")
)
if no_repeat_ngram_size > 0: if no_repeat_ngram_size > 0:
# calculate a list of banned tokens to prevent repetitively generating the same ngrams # calculate a list of banned tokens to prevent repetitively generating the same ngrams
@@ -992,7 +990,6 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin):
) # (batch_size, num_beams * vocab_size) ) # (batch_size, num_beams * vocab_size)
next_scores, next_tokens = tf.math.top_k(next_scores, k=2 * num_beams, sorted=True) next_scores, next_tokens = tf.math.top_k(next_scores, k=2 * num_beams, sorted=True)
print(next_tokens)
assert shape_list(next_scores) == shape_list(next_tokens) == [batch_size, 2 * num_beams] assert shape_list(next_scores) == shape_list(next_tokens) == [batch_size, 2 * num_beams]