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change dtype of pooling mask to 'int32' for Paddle2ONNX #39314

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merged 3 commits into from
Feb 10, 2022
Merged

change dtype of pooling mask to 'int32' for Paddle2ONNX #39314

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084a247
change dtype of pooling mask to 'int32' for Paddle2ONNX
weisy11 Jan 28, 2022
b52b9e3
empty commit to rerun ci
weisy11 Jan 28, 2022
704233d
fix format
weisy11 Jan 29, 2022
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12 changes: 6 additions & 6 deletions python/paddle/nn/functional/pooling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -611,7 +611,7 @@ def max_pool1d(x,
helper = LayerHelper(op_type, **locals())
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference('int32')
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down Expand Up @@ -1053,7 +1053,7 @@ def max_pool2d(x,
'max_pool2d')
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference("int32")
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down Expand Up @@ -1183,7 +1183,7 @@ def max_pool3d(x,
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'max_pool3d')
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference('int32')
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down Expand Up @@ -1559,7 +1559,7 @@ def adaptive_max_pool1d(x, output_size, return_mask=False, name=None):
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)

mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference('int32')
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down Expand Up @@ -1647,7 +1647,7 @@ def adaptive_max_pool2d(x, output_size, return_mask=False, name=None):
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)

mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference('int32')
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down Expand Up @@ -1740,7 +1740,7 @@ def adaptive_max_pool3d(x, output_size, return_mask=False, name=None):
dtype = helper.input_dtype(input_param_name='x')
pool_out = helper.create_variable_for_type_inference(dtype)

mask = helper.create_variable_for_type_inference(dtype)
mask = helper.create_variable_for_type_inference('int32')
outputs = {"Out": pool_out, "Mask": mask}

helper.append_op(
Expand Down