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[cherry pick] cherry pick from remove paddle.where #38849

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Jan 11, 2022
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[cherry pick] cherry pick from remove paddle.where #38849

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34 changes: 13 additions & 21 deletions python/paddle/nn/functional/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1650,25 +1650,16 @@ def cross_entropy(input,
label = paddle.unsqueeze(label, axis=axis)
if in_dygraph_mode():
if soft_label == False:
valid_label = paddle.where(label == ignore_index,
paddle.zeros_like(label), label)
# TODO: Temporarily use paddle.nonzero instead of paddle.max
# to detect and find out possible illegal label values
if len(paddle.nonzero(valid_label < 0)) > 0:
invalid_label = paddle.gather_nd(
valid_label, paddle.nonzero(valid_label < 0))
raise ValueError(
"Target({}) is out of class_dimension's lower bound({})".
format(invalid_label[0], 0))
# TODO: Temporarily use paddle.nonzero instead of paddle.max
# to detect and find out possible illegal label values
if len(paddle.nonzero(valid_label >= input.shape[axis])) > 0:
invalid_label = paddle.gather_nd(
valid_label,
paddle.nonzero(valid_label >= input.shape[axis]))
raise ValueError(
"Target({}) is out of class_dimension's upper bound({})".
format(invalid_label[0], input.shape[axis] - 1))
valid_label = paddle.cast(
label != ignore_index, dtype=label.dtype) * label
label_min = paddle.min(valid_label)
label_max = paddle.max(valid_label)
if label_min < 0:
raise ValueError("label should not out of bound, but got{}".
format(label_min))
if label_max >= input.shape[axis]:
raise ValueError("label should not out of bound, but got{}".
format(label_max))

_, out = _C_ops.softmax_with_cross_entropy(
input, label, 'soft_label', soft_label, 'ignore_index',
Expand Down Expand Up @@ -1817,8 +1808,9 @@ def cross_entropy(input,
"when weight is provided"\
.format(input.shape[axis], weight.shape[-1]))

valid_label = paddle.where(label == ignore_index,
paddle.zeros_like(label), label)
valid_label = paddle.multiply(
paddle.cast(
label != ignore_index, dtype=label.dtype), label)
ignore_weight_mask = paddle.cast((label != ignore_index),
input.dtype)
if ignore_weight_mask.ndim > 1 and ignore_weight_mask.shape[
Expand Down