fix conv3d_transpose_test timeout error (#25004)
* test=develop fix conv3d_transpose_test errorfix_copy_if_different
FDInSky
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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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import paddle.fluid.core as core
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import paddle.fluid as fluid
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from op_test import OpTest
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from test_conv3d_transpose_op import conv3dtranspose_forward_naive, TestConv3dTransposeOp
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class TestWithSymmetricPad_NHWC(TestConv3dTransposeOp):
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def init_test_case(self):
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self.pad = [1, 1, 1]
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self.stride = [1, 1, 1]
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self.dilations = [1, 1, 1]
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self.groups = 1
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self.input_size = [2, 5, 5, 5, 3] # NDHWC
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f_c = self.input_size[-1]
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self.filter_size = [f_c, 6, 3, 3, 3]
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self.data_format = 'NHWC'
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class TestWithAsymmetricPad_NHWC(TestConv3dTransposeOp):
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def init_test_case(self):
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self.pad = [1, 0, 1, 0, 1, 2]
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self.stride = [1, 1, 1]
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self.dilations = [1, 1, 1]
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self.groups = 1
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self.input_size = [2, 5, 5, 5, 3] # NDHWC
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f_c = self.input_size[-1]
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self.filter_size = [f_c, 6, 3, 3, 3]
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self.data_format = 'NHWC'
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class TestWithGroups_NHWC(TestConv3dTransposeOp):
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def init_test_case(self):
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self.check_no_filter = True
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self.pad = [1, 1, 1]
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self.stride = [1, 1, 1]
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self.dilations = [1, 1, 1]
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self.groups = 2
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self.input_size = [2, 5, 5, 5, 4] # NDHWC
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f_c = self.input_size[-1]
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self.filter_size = [f_c, 3, 3, 3, 3]
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self.data_format = 'NHWC'
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class TestWithStride_NHWC(TestConv3dTransposeOp):
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def init_test_case(self):
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self.pad = [1, 1, 1]
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self.stride = [2, 2, 2]
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self.dilations = [1, 1, 1]
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self.groups = 1
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self.input_size = [2, 5, 5, 5, 3] # NCDHW
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f_c = self.input_size[-1]
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self.filter_size = [f_c, 6, 3, 3, 3]
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self.data_format = 'NHWC'
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class TestWithDilation_NHWC(TestConv3dTransposeOp):
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def init_test_case(self):
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self.check_no_input = True
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self.pad = [1, 1, 1]
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self.stride = [1, 1, 1]
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self.dilations = [2, 2, 2]
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self.groups = 1
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self.input_size = [2, 5, 5, 5, 3] # NCDHW
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f_c = self.input_size[-1]
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self.filter_size = [f_c, 6, 3, 3, 3]
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self.data_format = 'NHWC'
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class TestConv3dTransposeAPI(unittest.TestCase):
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def test_case1(self):
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data1 = fluid.layers.data(
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name='data1', shape=[3, 5, 5, 5], dtype='float32')
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data2 = fluid.layers.data(
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name='data2', shape=[5, 5, 5, 3], dtype='float32')
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out1 = fluid.layers.conv3d_transpose(
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input=data1,
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groups=1,
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num_filters=6,
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filter_size=3,
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data_format='NCDHW')
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out2 = fluid.layers.conv3d_transpose(
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input=data2,
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groups=1,
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num_filters=6,
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filter_size=3,
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data_format='NDHWC')
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out3 = fluid.layers.conv3d_transpose(
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input=data1,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding=[[0, 0], [0, 0], [1, 1], [0, 0], [1, 1]],
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data_format='NCDHW')
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out4 = fluid.layers.conv3d_transpose(
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input=data2,
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groups=3,
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num_filters=6,
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filter_size=3,
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padding=[[0, 0], [0, 0], [1, 1], [1, 2], [0, 0]],
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data_format='NDHWC')
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out5 = fluid.layers.conv3d_transpose(
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input=data2,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding='SAME',
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data_format='NCDHW')
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out6 = fluid.layers.conv3d_transpose(
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input=data2,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding='VALID',
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data_format='NDHWC')
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out7 = fluid.layers.conv3d_transpose(
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input=data2,
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groups=1,
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num_filters=6,
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output_size=[7, 7, 7],
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padding=[0, 0, 0],
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data_format='NDHWC')
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data1_np = np.random.random((2, 3, 5, 5, 5)).astype("float32")
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data2_np = np.random.random((2, 5, 5, 5, 3)).astype("float32")
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if core.is_compiled_with_cuda():
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place = core.CUDAPlace(0)
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else:
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place = core.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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results = exe.run(
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fluid.default_main_program(),
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feed={"data1": data1_np,
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"data2": data2_np},
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fetch_list=[out1, out2, out3, out4, out5, out6, out7],
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return_numpy=True)
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self.assertIsNotNone(results[0])
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self.assertIsNotNone(results[1])
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self.assertIsNotNone(results[2])
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self.assertIsNotNone(results[3])
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self.assertIsNotNone(results[4])
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self.assertIsNotNone(results[5])
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self.assertIsNotNone(results[6])
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class TestConv3dTransposeOpException(unittest.TestCase):
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def test_exception(self):
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data = fluid.layers.data(
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name='data', shape=[3, 5, 5, 5], dtype="float32")
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def attr_data_format():
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out = fluid.layers.conv2d_transpose(
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input=data,
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groups=1,
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num_filters=6,
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filter_size=3,
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data_format="NCDW")
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self.assertRaises(ValueError, attr_data_format)
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def attr_padding_str():
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out = fluid.layers.conv2d_transpose(
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input=data,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding='Vald')
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self.assertRaises(ValueError, attr_padding_str)
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def attr_padding_list():
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out = fluid.layers.conv2d_transpose(
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input=data,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding=[[1, 1], [1, 1], [0, 0], [0, 0], [1, 1]])
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self.assertRaises(ValueError, attr_padding_list)
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def attr_padding_with_data_format():
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out = fluid.layers.conv2d_transpose(
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input=data,
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groups=1,
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num_filters=6,
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filter_size=3,
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padding=[[1, 1], [0, 0], [0, 0], [1, 0], [1, 1]],
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data_format='NDHWC')
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self.assertRaises(ValueError, attr_padding_with_data_format)
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if __name__ == '__main__':
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unittest.main()
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