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fix type promotion problem. #8414

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merged 5 commits into from
May 11, 2024
Merged

fix type promotion problem. #8414

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f03c9bc
fix type promotion problem.
zxcd May 10, 2024
b95be26
fix
zxcd May 10, 2024
b5e9b18
fix
zxcd May 10, 2024
7c90740
fix
zxcd May 10, 2024
aa3fa1c
fix
zxcd May 10, 2024
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fix
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@zxcd
zxcd committed May 10, 2024
commit 7c907408e66b4535c791120f3eea6dc06ea8961e
4 changes: 3 additions & 1 deletion paddlenlp/transformers/electra/modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1051,7 +1051,9 @@ def get_discriminator_inputs(self, inputs, raw_inputs, generator_logits, generat
mask_positions = paddle.where(generator_labels == -100, umask_positions, mask_positions)
updated_inputs = self.update_inputs(inputs, sampled_tokids, mask_positions)
# use inputs and updated_input to get discriminator labels
labels = mask_positions * (paddle.ones_like(inputs) - paddle.equal(updated_inputs, raw_inputs).astype("int64"))
labels = mask_positions * (
paddle.ones_like(inputs) - paddle.equal(updated_inputs, raw_inputs).astype(raw_inputs.dtype)
)
return updated_inputs, labels, sampled_tokids

def sample_from_softmax(self, logits, use_softmax_sample=True):
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5 changes: 2 additions & 3 deletions paddlenlp/transformers/prophetnet/modeling.py
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Expand Up @@ -82,9 +82,8 @@ def compute_relative_buckets(num_buckets, max_distance, relative_positions, is_b
) / math.log(max_distance / max_exact) * (num_buckets - max_exact)
val_if_large_num_buckets = paddle.ones_like(val_if_large) * (num_buckets - 1)
val_if_large_lt = paddle.cast(paddle.less_than(val_if_large, val_if_large_num_buckets), dtype=paddle.int32)
val_if_large = (
paddle.cast(val_if_large_lt * val_if_large, dtype=paddle.int32)
+ (1 - val_if_large_lt) * val_if_large_num_buckets
val_if_large = paddle.cast(val_if_large_lt * val_if_large, dtype=paddle.int32) + paddle.cast(
(1 - val_if_large_lt) * val_if_large_num_buckets, dtype=paddle.int32
)
rel_positions_bucket = rel_positions_bucket + paddle.where(
is_small, paddle.cast(inv_relative_positions, dtype=paddle.int32), val_if_large
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