test_conv3d_op.py 10.4 KB
Newer Older
1
#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
D
dzhwinter 已提交
2
#
D
dzhwinter 已提交
3 4 5
# 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
D
dzhwinter 已提交
6
#
D
dzhwinter 已提交
7
#     http://www.apache.org/licenses/LICENSE-2.0
D
dzhwinter 已提交
8
#
D
dzhwinter 已提交
9 10 11 12 13 14
# 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.

C
chengduoZH 已提交
15 16
import unittest
import numpy as np
17

18
import paddle.fluid.core as core
19
from op_test import OpTest
C
chengduoZH 已提交
20 21


22 23 24 25 26
def conv3d_forward_naive(input, filter, group, conv_param):
    in_n, in_c, in_d, in_h, in_w = input.shape
    out_c, f_c, f_d, f_h, f_w = filter.shape
    assert f_c * group == in_c
    assert np.mod(out_c, group) == 0
M
minqiyang 已提交
27
    sub_out_c = out_c // group
28

C
chengduoZH 已提交
29 30 31
    stride, pad, dilation = conv_param['stride'], conv_param['pad'], conv_param[
        'dilations']

M
minqiyang 已提交
32 33 34
    out_d = 1 + (in_d + 2 * pad[0] - (dilation[0] * (f_d - 1) + 1)) // stride[0]
    out_h = 1 + (in_h + 2 * pad[1] - (dilation[1] * (f_h - 1) + 1)) // stride[1]
    out_w = 1 + (in_w + 2 * pad[2] - (dilation[2] * (f_w - 1) + 1)) // stride[2]
C
chengduoZH 已提交
35

36 37
    out = np.zeros((in_n, out_c, out_d, out_h, out_w))

C
chengduoZH 已提交
38 39 40 41
    d_bolck_d = (dilation[0] * (f_d - 1) + 1)
    d_bolck_h = (dilation[1] * (f_h - 1) + 1)
    d_bolck_w = (dilation[2] * (f_w - 1) + 1)

42 43 44 45
    input_pad = np.pad(input, ((0, ), (0, ), (pad[0], ), (pad[1], ),
                               (pad[2], )),
                       mode='constant',
                       constant_values=0)
C
chengduoZH 已提交
46 47 48 49 50

    filter_dilation = np.zeros((out_c, f_c, d_bolck_d, d_bolck_h, d_bolck_w))
    filter_dilation[:, :, 0:d_bolck_d:dilation[0], 0:d_bolck_h:dilation[1], 0:
                    d_bolck_w:dilation[2]] = filter

51 52 53 54 55 56
    for d in range(out_d):
        for i in range(out_h):
            for j in range(out_w):
                for g in range(group):
                    input_pad_masked = \
                        input_pad[:, g * f_c:(g + 1) * f_c,
C
chengduoZH 已提交
57 58 59 60 61 62
                        d * stride[0]:d * stride[0] + d_bolck_d,
                        i * stride[1]:i * stride[1] + d_bolck_h,
                        j * stride[2]:j * stride[2] + d_bolck_w]

                    f_sub = filter_dilation[g * sub_out_c:(g + 1) *
                                            sub_out_c, :, :, :, :]
63 64 65
                    for k in range(sub_out_c):
                        out[:, g * sub_out_c + k, d, i, j] = \
                            np.sum(input_pad_masked * f_sub[k, :, :, :, :],
C
chengduoZH 已提交
66
                                   axis=(1, 2, 3, 4))
67 68 69 70

    return out


C
chengduoZH 已提交
71 72
class TestConv3dOp(OpTest):
    def setUp(self):
K
Kexin Zhao 已提交
73
        self.op_type = "conv3d"
74
        self.use_cudnn = False
K
Kexin Zhao 已提交
75 76
        self.dtype = np.float32
        self.init_kernel_type()
77
        self.init_group()
C
chengduoZH 已提交
78
        self.init_dilation()
79 80
        self.init_test_case()

C
chengduoZH 已提交
81 82 83
        conv3d_param = {
            'stride': self.stride,
            'pad': self.pad,
84 85
            'dilations': self.dilations,
            'data_format': 'AnyLayout'  # TODO(dzhwinter) : should be fix latter
C
chengduoZH 已提交
86
        }
K
Kexin Zhao 已提交
87 88 89

        input = np.random.random(self.input_size).astype(self.dtype)
        filter = np.random.random(self.filter_size).astype(self.dtype)
C
chengduoZH 已提交
90
        output = conv3d_forward_naive(input, filter, self.groups,
K
Kexin Zhao 已提交
91
                                      conv3d_param).astype(self.dtype)
C
chengduoZH 已提交
92

K
Kexin Zhao 已提交
93 94 95 96
        self.inputs = {
            'Input': OpTest.np_dtype_to_fluid_dtype(input),
            'Filter': OpTest.np_dtype_to_fluid_dtype(filter)
        }
C
chengduoZH 已提交
97
        self.attrs = {
98 99
            'strides': self.stride,
            'paddings': self.pad,
C
chengduoZH 已提交
100
            'groups': self.groups,
K
Kexin Zhao 已提交
101 102
            'dilations': self.dilations,
            'use_cudnn': self.use_cudnn
C
chengduoZH 已提交
103 104 105
        }
        self.outputs = {'Output': output}

106 107 108
    def testcudnn(self):
        return core.is_compiled_with_cuda() and self.use_cudnn

C
chengduoZH 已提交
109
    def test_check_output(self):
110
        if self.testcudnn():
111 112 113 114
            place = core.CUDAPlace(0)
            self.check_output_with_place(place, atol=1e-5)
        else:
            self.check_output()
C
chengduoZH 已提交
115 116

    def test_check_grad(self):
K
Kexin Zhao 已提交
117 118
        if self.dtype == np.float16:
            return
119
        if self.testcudnn():
120 121 122 123 124 125 126 127 128
            place = core.CUDAPlace(0)
            self.check_grad_with_place(
                place,
                set(['Input', 'Filter']),
                'Output',
                max_relative_error=0.03)
        else:
            self.check_grad(
                set(['Input', 'Filter']), 'Output', max_relative_error=0.03)
C
chengduoZH 已提交
129

C
chengduoZH 已提交
130
    def test_check_grad_no_filter(self):
K
Kexin Zhao 已提交
131 132
        if self.dtype == np.float16:
            return
133
        if self.testcudnn():
134 135 136 137 138 139 140 141 142 143 144 145
            place = core.CUDAPlace(0)
            self.check_grad_with_place(
                place, ['Input'],
                'Output',
                max_relative_error=0.03,
                no_grad_set=set(['Filter']))
        else:
            self.check_grad(
                ['Input'],
                'Output',
                max_relative_error=0.03,
                no_grad_set=set(['Filter']))
C
chengduoZH 已提交
146 147

    def test_check_grad_no_input(self):
K
Kexin Zhao 已提交
148 149
        if self.dtype == np.float16:
            return
150
        if self.testcudnn():
151 152 153 154 155 156 157 158 159 160 161 162
            place = core.CUDAPlace(0)
            self.check_grad_with_place(
                place, ['Filter'],
                'Output',
                max_relative_error=0.03,
                no_grad_set=set(['Input']))
        else:
            self.check_grad(
                ['Filter'],
                'Output',
                max_relative_error=0.03,
                no_grad_set=set(['Input']))
C
chengduoZH 已提交
163

164 165 166
    def init_test_case(self):
        self.pad = [0, 0, 0]
        self.stride = [1, 1, 1]
C
chengduoZH 已提交
167
        self.input_size = [2, 3, 4, 4, 4]  # NCDHW
168
        assert np.mod(self.input_size[1], self.groups) == 0
M
minqiyang 已提交
169
        f_c = self.input_size[1] // self.groups
170 171
        self.filter_size = [6, f_c, 3, 3, 3]

C
chengduoZH 已提交
172 173 174
    def init_dilation(self):
        self.dilations = [1, 1, 1]

175
    def init_group(self):
C
chengduoZH 已提交
176 177
        self.groups = 1

K
Kexin Zhao 已提交
178 179
    def init_kernel_type(self):
        pass
180

C
chengduoZH 已提交
181

C
chengduoZH 已提交
182 183 184 185
class TestCase1(TestConv3dOp):
    def init_test_case(self):
        self.pad = [1, 1, 1]
        self.stride = [1, 1, 1]
C
chengduoZH 已提交
186
        self.input_size = [2, 3, 4, 4, 4]  # NCDHW
C
chengduoZH 已提交
187
        assert np.mod(self.input_size[1], self.groups) == 0
M
minqiyang 已提交
188
        f_c = self.input_size[1] // self.groups
C
chengduoZH 已提交
189 190 191
        self.filter_size = [6, f_c, 3, 3, 3]


C
chengduoZH 已提交
192 193 194
class TestWithGroup1(TestConv3dOp):
    def init_group(self):
        self.groups = 3
C
chengduoZH 已提交
195 196


C
chengduoZH 已提交
197
class TestWithGroup2(TestCase1):
198
    def init_group(self):
C
chengduoZH 已提交
199 200
        self.groups = 3

201

C
chengduoZH 已提交
202 203 204 205 206 207
class TestWith1x1(TestConv3dOp):
    def init_test_case(self):
        self.pad = [0, 0, 0]
        self.stride = [1, 1, 1]
        self.input_size = [2, 3, 4, 4, 4]  # NCHW
        assert np.mod(self.input_size[1], self.groups) == 0
M
minqiyang 已提交
208
        f_c = self.input_size[1] // self.groups
C
chengduoZH 已提交
209 210 211 212
        self.filter_size = [6, f_c, 1, 1, 1]

    def init_dilation(self):
        self.dilations = [1, 1, 1]
C
chengduoZH 已提交
213

C
chengduoZH 已提交
214 215 216
    def init_group(self):
        self.groups = 3

C
chengduoZH 已提交
217

218 219 220 221 222 223
class TestWithInput1x1Filter1x1(TestConv3dOp):
    def init_test_case(self):
        self.pad = [0, 0, 0]
        self.stride = [1, 1, 1]
        self.input_size = [2, 3, 1, 1, 1]  # NCHW
        assert np.mod(self.input_size[1], self.groups) == 0
M
minqiyang 已提交
224
        f_c = self.input_size[1] // self.groups
225 226 227 228 229 230 231 232 233
        self.filter_size = [6, f_c, 1, 1, 1]

    def init_dilation(self):
        self.dilations = [1, 1, 1]

    def init_group(self):
        self.groups = 3


C
chengduoZH 已提交
234 235 236 237 238 239
class TestWithDilation(TestConv3dOp):
    def init_test_case(self):
        self.pad = [0, 0, 0]
        self.stride = [1, 1, 1]
        self.input_size = [2, 3, 6, 6, 6]  # NCDHW
        assert np.mod(self.input_size[1], self.groups) == 0
M
minqiyang 已提交
240
        f_c = self.input_size[1] // self.groups
C
chengduoZH 已提交
241 242 243 244 245 246 247
        self.filter_size = [6, f_c, 2, 2, 2]

    def init_dilation(self):
        self.dilations = [2, 2, 2]

    def init_group(self):
        self.groups = 3
C
chengduoZH 已提交
248

C
chengduoZH 已提交
249

K
Kexin Zhao 已提交
250
#----------------Conv3dCUDNN----------------
251
class TestCUDNN(TestConv3dOp):
K
Kexin Zhao 已提交
252
    def init_kernel_type(self):
253
        self.use_cudnn = True
K
Kexin Zhao 已提交
254 255 256 257 258 259 260 261 262 263 264 265


class TestFP16CUDNN(TestConv3dOp):
    def init_kernel_type(self):
        self.use_cudnn = True
        self.dtype = np.float16

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            place = core.CUDAPlace(0)
            if core.is_float16_supported(place):
                self.check_output_with_place(place, atol=2e-2)
武毅 已提交
266 267


268
class TestWithGroup1CUDNN(TestWithGroup1):
K
Kexin Zhao 已提交
269
    def init_kernel_type(self):
270
        self.use_cudnn = True
K
Kexin Zhao 已提交
271 272 273 274 275 276 277 278 279 280 281 282


class TestFP16WithGroup1CUDNN(TestWithGroup1):
    def init_kernel_type(self):
        self.use_cudnn = True
        self.dtype = np.float16

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            place = core.CUDAPlace(0)
            if core.is_float16_supported(place):
                self.check_output_with_place(place, atol=2e-2)
武毅 已提交
283 284


285
class TestWithGroup2CUDNN(TestWithGroup2):
K
Kexin Zhao 已提交
286
    def init_kernel_type(self):
287
        self.use_cudnn = True
K
Kexin Zhao 已提交
288 289 290 291 292 293 294 295 296 297 298 299


class TestFP16WithGroup2CUDNN(TestWithGroup2):
    def init_kernel_type(self):
        self.use_cudnn = True
        self.dtype = np.float16

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            place = core.CUDAPlace(0)
            if core.is_float16_supported(place):
                self.check_output_with_place(place, atol=2e-2)
武毅 已提交
300 301


302
class TestWith1x1CUDNN(TestWith1x1):
K
Kexin Zhao 已提交
303
    def init_kernel_type(self):
304
        self.use_cudnn = True
K
Kexin Zhao 已提交
305 306 307 308 309 310 311 312 313 314 315 316


class TestFP16With1x1CUDNN(TestWith1x1):
    def init_kernel_type(self):
        self.use_cudnn = True
        self.dtype = np.float16

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            place = core.CUDAPlace(0)
            if core.is_float16_supported(place):
                self.check_output_with_place(place, atol=2e-2)
武毅 已提交
317 318


319
class TestWithInput1x1Filter1x1CUDNN(TestWithInput1x1Filter1x1):
K
Kexin Zhao 已提交
320
    def init_kernel_type(self):
321
        self.use_cudnn = True
K
Kexin Zhao 已提交
322 323 324 325 326 327 328 329 330 331 332 333


class TestFP16WithInput1x1Filter1x1CUDNN(TestWithInput1x1Filter1x1):
    def init_kernel_type(self):
        self.use_cudnn = True
        self.dtype = np.float16

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            place = core.CUDAPlace(0)
            if core.is_float16_supported(place):
                self.check_output_with_place(place, atol=2e-2)
334 335


武毅 已提交
336 337
# FIXME(typhoonzero): find a way to determine if
# using cudnn > 6 in python
338
# class TestWithDilationCUDNN(TestWithDilation):
武毅 已提交
339
#     def init_op_type(self):
340
#         self.op_type = "conv3d"
武毅 已提交
341

C
chengduoZH 已提交
342 343
if __name__ == '__main__':
    unittest.main()