From 084a247724f1e9daeff7306c928f74b901e7994e Mon Sep 17 00:00:00 2001 From: weishengyu Date: Fri, 28 Jan 2022 15:44:45 +0800 Subject: [PATCH 1/3] change dtype of pooling mask to 'int32' for Paddle2ONNX --- python/paddle/nn/functional/pooling.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/python/paddle/nn/functional/pooling.py b/python/paddle/nn/functional/pooling.py index db9665f7a32c4d..01ddf05fb82d29 100755 --- a/python/paddle/nn/functional/pooling.py +++ b/python/paddle/nn/functional/pooling.py @@ -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( @@ -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( @@ -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( @@ -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( @@ -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( @@ -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( From b52b9e3be618fc65cc3c9765b6cf20dd6547c3a3 Mon Sep 17 00:00:00 2001 From: weishengyu Date: Fri, 28 Jan 2022 15:54:58 +0800 Subject: [PATCH 2/3] empty commit to rerun ci --- python/paddle/nn/functional/pooling.py | 1 + 1 file changed, 1 insertion(+) diff --git a/python/paddle/nn/functional/pooling.py b/python/paddle/nn/functional/pooling.py index 01ddf05fb82d29..de87792170aae7 100755 --- a/python/paddle/nn/functional/pooling.py +++ b/python/paddle/nn/functional/pooling.py @@ -1144,6 +1144,7 @@ def max_pool3d(x, return_mask=True) # output.shape [None, 3, 16, 16, 16], max_indices.shape [None, 3, 16, 16, 16], """ + kernel_size = utils.convert_to_list(kernel_size, 3, 'pool_size') if stride is None: stride = kernel_size From 704233dbac9338509b0da8cd93cc44fb2430aed3 Mon Sep 17 00:00:00 2001 From: Wei Shengyu Date: Sat, 29 Jan 2022 15:37:02 +0800 Subject: [PATCH 3/3] fix format --- python/paddle/nn/functional/pooling.py | 1 - 1 file changed, 1 deletion(-) diff --git a/python/paddle/nn/functional/pooling.py b/python/paddle/nn/functional/pooling.py index de87792170aae7..01ddf05fb82d29 100755 --- a/python/paddle/nn/functional/pooling.py +++ b/python/paddle/nn/functional/pooling.py @@ -1144,7 +1144,6 @@ def max_pool3d(x, return_mask=True) # output.shape [None, 3, 16, 16, 16], max_indices.shape [None, 3, 16, 16, 16], """ - kernel_size = utils.convert_to_list(kernel_size, 3, 'pool_size') if stride is None: stride = kernel_size