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Fix conv transpose (#28629)

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* fix conv_transpose unittest. test=develop
musl/fix_failed_unittests_in_musl
Kaipeng Deng 4 years ago committed by GitHub
parent bff4179cc7
commit ed7aa8f9c3
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 121 additions and 117 deletions
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5
python/paddle/fluid/tests/unittests/CMakeLists.txt
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@ -75,8 +75,6 @@ if(NOT WITH_GPU OR WIN32)
LIST(REMOVE_ITEM TEST_OPS test_collective_allgather_api)
endif()
#TODO(sunxiaolong01): Fix this unitest failed on GCC8.
LIST(REMOVE_ITEM TEST_OPS test_conv2d_transpose_op)
if(WIN32)
LIST(REMOVE_ITEM TEST_OPS test_boxps)
LIST(REMOVE_ITEM TEST_OPS test_trainer_desc)
@ -341,7 +339,6 @@ list(REMOVE_ITEM TEST_OPS test_fuse_bn_act_pass)
list(REMOVE_ITEM TEST_OPS test_fuse_bn_add_act_pass)
list(REMOVE_ITEM TEST_OPS test_imperative_static_runner_mnist)
list(REMOVE_ITEM TEST_OPS test_imperative_static_runner_while)
list(REMOVE_ITEM TEST_OPS test_conv3d_transpose_op)
# disable this unittest temporarily
list(REMOVE_ITEM TEST_OPS test_imperative_data_loader_exception)
@ -697,7 +694,9 @@ set_tests_properties(test_eager_deletion_lstm_net PROPERTIES TIMEOUT 120)
set_tests_properties(test_parallel_executor_mnist PROPERTIES TIMEOUT 120)
set_tests_properties(test_imperative_ptb_rnn PROPERTIES TIMEOUT 120)
set_tests_properties(test_imperative_save_load_v2 PROPERTIES TIMEOUT 120)
set_tests_properties(test_conv2d_transpose_op PROPERTIES TIMEOUT 120)
set_tests_properties(test_conv3d_transpose_part2_op PROPERTIES TIMEOUT 120)
set_tests_properties(test_conv3d_transpose_op PROPERTIES TIMEOUT 120)
set_tests_properties(test_prroi_pool_op PROPERTIES TIMEOUT 120)
set_tests_properties(test_multiprocess_dataloader_iterable_dataset_static PROPERTIES TIMEOUT 120)
set_tests_properties(test_lstm_cudnn_op PROPERTIES TIMEOUT 120)

97
python/paddle/fluid/tests/unittests/test_conv2d_transpose_op.py
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@ -17,6 +17,8 @@ from __future__ import print_function
import unittest
import numpy as np
import paddle
paddle.enable_static()
import paddle.fluid.core as core
import paddle.fluid as fluid
from op_test import OpTest
@ -654,101 +656,6 @@ class TestCUDNNWithEvenUpsample_NHWC(TestWithEvenUpsample):
self.op_type = "conv2d_transpose"
class TestDepthwiseConvTranspose(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 8, 16, 16] # NCHW
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 4, 4]
self.op_type = "depthwise_conv2d_transpose"
class TestDepthwiseConvTransposeAsymmetricPad(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 8, 16, 16] # NCHW
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NCHW'
class TestDepthwiseConvTransposeSAMEPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 8, 16, 16] # NHWC
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.padding_algorithm = 'SAME'
class TestDepthwiseConvTransposeVALIDPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 8, 16, 16] # NHWC
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.padding_algorithm = 'VALID'
class TestDepthwiseConvTranspose_NHWC_4x4kernel(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 16, 16, 8] # NHWC
self.groups = 8
assert np.mod(self.input_size[3], self.groups) == 0
f_c = self.input_size[3] // self.groups
self.filter_size = [self.input_size[3], f_c, 4, 4]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NHWC'
class TestDepthwiseConvTranspose_NHWC_3x3kernel(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 16, 16, 8] # NHWC
self.groups = 8
assert np.mod(self.input_size[3], self.groups) == 0
f_c = self.input_size[3] // self.groups
self.filter_size = [self.input_size[3], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NHWC'
class TestDepthwiseConvTransposeAsymmetricPad_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [2, 2]
self.dilations = [1, 1]
self.input_size = [2, 16, 16, 8] # NHWC
self.groups = 8
assert np.mod(self.input_size[3], self.groups) == 0
f_c = self.input_size[3] // self.groups
self.filter_size = [self.input_size[3], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NHWC'
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN_FP16(TestConv2DTransposeOp):

96
python/paddle/fluid/tests/unittests/test_conv2d_transpose_op_depthwise_conv.py
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@ -0,0 +1,96 @@
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import unittest
import numpy as np
import paddle
paddle.enable_static()
import paddle.fluid.core as core
import paddle.fluid as fluid
from op_test import OpTest
from test_conv2d_transpose_op import TestConv2DTransposeOp
class TestDepthwiseConvTranspose(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
self.dilations = [1, 1]
self.input_size = [1, 8, 4, 4] # NCHW
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 4, 4]
self.op_type = "depthwise_conv2d_transpose"
class TestDepthwiseConvTransposeAsymmetricPad(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1, 1, 2]
self.stride = [1, 1]
self.dilations = [1, 1]
self.input_size = [1, 8, 4, 4] # NCHW
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NCHW'
class TestDepthwiseConvTransposeSAMEPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [1, 1]
self.dilations = [1, 1]
self.input_size = [1, 8, 4, 4] # NHWC
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.padding_algorithm = 'SAME'
class TestDepthwiseConvTransposeVALIDPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [1, 1]
self.dilations = [1, 1]
self.input_size = [1, 8, 4, 4] # NHWC
self.groups = 8
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
self.filter_size = [self.input_size[1], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.padding_algorithm = 'VALID'
class TestDepthwiseConvTranspose_NHWC_3x3kernel(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
self.dilations = [1, 1]
self.input_size = [1, 4, 4, 8] # NHWC
self.groups = 8
assert np.mod(self.input_size[3], self.groups) == 0
f_c = self.input_size[3] // self.groups
self.filter_size = [self.input_size[3], f_c, 3, 3]
self.op_type = "depthwise_conv2d_transpose"
self.data_format = 'NHWC'
if __name__ == '__main__':
unittest.main()

40
python/paddle/fluid/tests/unittests/test_conv3d_transpose_op.py
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@ -17,6 +17,8 @@ from __future__ import print_function
import unittest
import numpy as np
import paddle
paddle.enable_static()
import paddle.fluid.core as core
import paddle.fluid as fluid
from op_test import OpTest
@ -207,7 +209,7 @@ class TestWithSymmetricPad(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -218,7 +220,7 @@ class TestWithAsymmetricPad(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -228,7 +230,7 @@ class TestWithSAMEPad(TestConv3DTransposeOp):
self.stride = [1, 1, 2]
self.dilations = [1, 2, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 6] # NCDHW
self.input_size = [1, 2, 5, 5, 6] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 4]
self.padding_algorithm = 'SAME'
@ -239,7 +241,7 @@ class TestWithVALIDPad(TestConv3DTransposeOp):
self.stride = [2, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 4, 3]
self.padding_algorithm = 'VALID'
@ -252,7 +254,7 @@ class TestWithStride(TestConv3DTransposeOp):
self.stride = [2, 2, 2]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -263,7 +265,7 @@ class TestWithGroups(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 2
self.input_size = [2, 4, 5, 5, 5] # NCHW
self.input_size = [1, 2, 5, 5, 5] # NCHW
f_c = self.input_size[1]
self.filter_size = [f_c, 3, 3, 3, 3]
@ -274,7 +276,7 @@ class TestWithDilation(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [2, 2, 2]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -285,7 +287,7 @@ class Test_NHWC(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 5, 5, 5, 3] # NDHWC
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.data_format = 'NHWC'
@ -308,7 +310,7 @@ class TestCUDNNWithSymmetricPad(TestWithSymmetricPad):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -325,7 +327,7 @@ class TestCUDNNWithAsymmetricPad(TestWithAsymmetricPad):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 4, 4, 4] # NCDHW
self.input_size = [1, 2, 4, 4, 4] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -341,7 +343,7 @@ class TestCUDNNWithSAMEPad(TestWithSAMEPad):
self.stride = [1, 1, 2]
self.dilations = [1, 2, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 4, 3]
self.padding_algorithm = 'SAME'
@ -358,7 +360,7 @@ class TestCUDNNWithVALIDPad(TestWithVALIDPad):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.padding_algorithm = 'VALID'
@ -376,7 +378,7 @@ class TestCUDNNWithStride(TestWithStride):
self.stride = [2, 2, 2]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 3, 5, 5, 5] # NCDHW
self.input_size = [1, 2, 5, 5, 5] # NCDHW
f_c = self.input_size[1]
self.filter_size = [f_c, 6, 3, 3, 3]
@ -393,7 +395,7 @@ class TestCUDNNWithGroups(TestWithGroups):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 2
self.input_size = [2, 4, 5, 5, 5] # NCHW
self.input_size = [1, 2, 5, 5, 5] # NCHW
f_c = self.input_size[1]
self.filter_size = [f_c, 3, 3, 3, 3]
@ -425,7 +427,7 @@ class TestCUDNN_NHWC(TestConv3DTransposeOp):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 5, 5, 5, 3] # NDHWC
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.data_format = 'NHWC'
@ -443,7 +445,7 @@ class TestCUDNNWithSymmetricPad_NHWC(TestWithSymmetricPad):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 5, 5, 5, 3] # NDHWC
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.data_format = 'NHWC'
@ -461,7 +463,7 @@ class TestCUDNNWithAsymmetricPad_NHWC(TestWithAsymmetricPad):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 5, 5, 5, 3] # NDHWC
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.data_format = 'NHWC'
@ -479,7 +481,7 @@ class TestCUDNNWithStride_NHWC(TestWithStride):
self.stride = [2, 2, 2]
self.dilations = [1, 1, 1]
self.groups = 1
self.input_size = [2, 5, 5, 5, 3] # NCDHW
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 6, 3, 3, 3]
self.data_format = 'NHWC'
@ -497,7 +499,7 @@ class TestCUDNNWithGroups_NHWC(TestWithGroups):
self.stride = [1, 1, 1]
self.dilations = [1, 1, 1]
self.groups = 2
self.input_size = [2, 5, 5, 5, 4] # NCHW
self.input_size = [1, 5, 5, 5, 2] # NDHWC
f_c = self.input_size[-1]
self.filter_size = [f_c, 3, 3, 3, 3]
self.data_format = 'NHWC'

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