test_pool2d_op.py 9.8 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 27
def max_pool2D_forward_naive(x,
                             ksize,
                             strides,
                             paddings,
                             global_pool=0,
                             ceil_mode=False):
C
chengduoZH 已提交
28
    N, C, H, W = x.shape
C
chengduoZH 已提交
29 30
    if global_pool == 1:
        ksize = [H, W]
31
    H_out = (H - ksize[0] + 2 * paddings[0] + strides[0] - 1
M
minqiyang 已提交
32 33
             ) // strides[0] + 1 if ceil_mode else (
                 H - ksize[0] + 2 * paddings[0]) // strides[0] + 1
34
    W_out = (W - ksize[1] + 2 * paddings[1] + strides[1] - 1
M
minqiyang 已提交
35 36
             ) // strides[1] + 1 if ceil_mode else (
                 W - ksize[1] + 2 * paddings[1]) // strides[1] + 1
C
chengduoZH 已提交
37
    out = np.zeros((N, C, H_out, W_out))
38 39
    for i in range(H_out):
        for j in range(W_out):
C
chengduoZH 已提交
40 41 42 43 44 45 46 47 48 49
            r_start = np.max((i * strides[0] - paddings[0], 0))
            r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H))
            c_start = np.max((j * strides[1] - paddings[1], 0))
            c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W))
            x_masked = x[:, :, r_start:r_end, c_start:c_end]

            out[:, :, i, j] = np.max(x_masked, axis=(2, 3))
    return out


50 51 52 53 54 55
def avg_pool2D_forward_naive(x,
                             ksize,
                             strides,
                             paddings,
                             global_pool=0,
                             ceil_mode=False):
C
chengduoZH 已提交
56
    N, C, H, W = x.shape
C
chengduoZH 已提交
57 58
    if global_pool == 1:
        ksize = [H, W]
59
    H_out = (H - ksize[0] + 2 * paddings[0] + strides[0] - 1
M
minqiyang 已提交
60 61
             ) // strides[0] + 1 if ceil_mode else (
                 H - ksize[0] + 2 * paddings[0]) // strides[0] + 1
62
    W_out = (W - ksize[1] + 2 * paddings[1] + strides[1] - 1
M
minqiyang 已提交
63 64
             ) // strides[1] + 1 if ceil_mode else (
                 W - ksize[1] + 2 * paddings[1]) // strides[1] + 1
C
chengduoZH 已提交
65
    out = np.zeros((N, C, H_out, W_out))
66 67
    for i in range(H_out):
        for j in range(W_out):
C
chengduoZH 已提交
68 69 70 71 72 73 74 75 76 77 78 79 80
            r_start = np.max((i * strides[0] - paddings[0], 0))
            r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H))
            c_start = np.max((j * strides[1] - paddings[1], 0))
            c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W))
            x_masked = x[:, :, r_start:r_end, c_start:c_end]

            out[:, :, i, j] = np.sum(x_masked, axis=(2, 3)) / (
                (r_end - r_start) * (c_end - c_start))
    return out


class TestPool2d_Op(OpTest):
    def setUp(self):
K
Kexin Zhao 已提交
81
        self.op_type = "pool2d"
82
        self.use_cudnn = False
83
        self.use_mkldnn = False
K
Kexin Zhao 已提交
84
        self.dtype = np.float32
C
chengduoZH 已提交
85
        self.init_test_case()
C
chengduoZH 已提交
86
        self.init_global_pool()
K
Kexin Zhao 已提交
87
        self.init_kernel_type()
C
chengduoZH 已提交
88
        self.init_pool_type()
89
        self.init_ceil_mode()
C
fix bug  
chengduoZH 已提交
90 91
        if self.global_pool:
            self.paddings = [0 for _ in range(len(self.paddings))]
K
Kexin Zhao 已提交
92
        input = np.random.random(self.shape).astype(self.dtype)
C
chengduoZH 已提交
93
        output = self.pool2D_forward_naive(input, self.ksize, self.strides,
94
                                           self.paddings, self.global_pool,
K
Kexin Zhao 已提交
95 96
                                           self.ceil_mode).astype(self.dtype)
        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(input)}
C
chengduoZH 已提交
97 98 99 100 101

        self.attrs = {
            'strides': self.strides,
            'paddings': self.paddings,
            'ksize': self.ksize,
C
chengduoZH 已提交
102 103
            'pooling_type': self.pool_type,
            'global_pooling': self.global_pool,
104
            'use_cudnn': self.use_cudnn,
105
            'use_mkldnn': self.use_mkldnn,
106
            'ceil_mode': self.ceil_mode,
107
            'data_format': 'AnyLayout'  # TODO(dzhwinter) : should be fix latter
C
chengduoZH 已提交
108 109
        }

K
Kexin Zhao 已提交
110
        self.outputs = {'Out': output}
C
chengduoZH 已提交
111

112 113 114
    def testcudnn(self):
        return core.is_compiled_with_cuda() and self.use_cudnn

C
chengduoZH 已提交
115
    def test_check_output(self):
116
        if self.testcudnn():
117 118 119 120
            place = core.CUDAPlace(0)
            self.check_output_with_place(place, atol=1e-5)
        else:
            self.check_output()
C
chengduoZH 已提交
121 122

    def test_check_grad(self):
K
Kexin Zhao 已提交
123 124
        if self.dtype == np.float16:
            return
125
        if self.testcudnn() and self.pool_type != "max":
126 127 128 129
            place = core.CUDAPlace(0)
            self.check_grad_with_place(
                place, set(['X']), 'Out', max_relative_error=0.07)
        elif self.pool_type != "max":
130
            self.check_grad(set(['X']), 'Out', max_relative_error=0.07)
C
chengduoZH 已提交
131

C
chengduoZH 已提交
132
    def init_test_case(self):
C
chengduoZH 已提交
133 134 135 136 137
        self.shape = [2, 3, 5, 5]
        self.ksize = [3, 3]
        self.strides = [1, 1]
        self.paddings = [0, 0]

K
Kexin Zhao 已提交
138 139
    def init_kernel_type(self):
        pass
C
chengduoZH 已提交
140 141 142

    def init_pool_type(self):
        self.pool_type = "avg"
C
chengduoZH 已提交
143 144 145 146
        self.pool2D_forward_naive = avg_pool2D_forward_naive

    def init_global_pool(self):
        self.global_pool = True
C
chengduoZH 已提交
147

148 149 150
    def init_ceil_mode(self):
        self.ceil_mode = False

C
chengduoZH 已提交
151

C
chengduoZH 已提交
152
class TestCase1(TestPool2d_Op):
C
chengduoZH 已提交
153
    def init_test_case(self):
C
chengduoZH 已提交
154
        self.shape = [2, 3, 7, 7]
C
chengduoZH 已提交
155 156
        self.ksize = [3, 3]
        self.strides = [1, 1]
C
chengduoZH 已提交
157
        self.paddings = [0, 0]
C
chengduoZH 已提交
158

C
chengduoZH 已提交
159 160
    def init_pool_type(self):
        self.pool_type = "avg"
C
chengduoZH 已提交
161 162 163 164
        self.pool2D_forward_naive = avg_pool2D_forward_naive

    def init_global_pool(self):
        self.global_pool = False
C
chengduoZH 已提交
165

C
chengduoZH 已提交
166

C
chengduoZH 已提交
167
class TestCase2(TestPool2d_Op):
C
chengduoZH 已提交
168
    def init_test_case(self):
C
chengduoZH 已提交
169
        self.shape = [2, 3, 7, 7]
C
chengduoZH 已提交
170 171 172 173
        self.ksize = [3, 3]
        self.strides = [1, 1]
        self.paddings = [1, 1]

C
chengduoZH 已提交
174 175
    def init_pool_type(self):
        self.pool_type = "avg"
C
chengduoZH 已提交
176
        self.pool2D_forward_naive = avg_pool2D_forward_naive
C
chengduoZH 已提交
177

C
chengduoZH 已提交
178 179
    def init_global_pool(self):
        self.global_pool = False
C
chengduoZH 已提交
180

C
chengduoZH 已提交
181

C
chengduoZH 已提交
182
class TestCase3(TestPool2d_Op):
C
chengduoZH 已提交
183 184
    def init_pool_type(self):
        self.pool_type = "max"
C
chengduoZH 已提交
185
        self.pool2D_forward_naive = max_pool2D_forward_naive
C
chengduoZH 已提交
186

C
chengduoZH 已提交
187 188

class TestCase4(TestCase1):
C
chengduoZH 已提交
189 190 191 192
    def init_pool_type(self):
        self.pool_type = "max"
        self.pool2D_forward_naive = max_pool2D_forward_naive

C
chengduoZH 已提交
193 194

class TestCase5(TestCase2):
C
chengduoZH 已提交
195 196
    def init_pool_type(self):
        self.pool_type = "max"
C
chengduoZH 已提交
197
        self.pool2D_forward_naive = max_pool2D_forward_naive
C
chengduoZH 已提交
198 199


200 201
#--------------------test pool2d--------------------
class TestCUDNNCase1(TestPool2d_Op):
K
Kexin Zhao 已提交
202
    def init_kernel_type(self):
203
        self.use_cudnn = True
C
chengduoZH 已提交
204 205


K
Kexin Zhao 已提交
206
class TestFP16CUDNNCase1(TestPool2d_Op):
K
Kexin Zhao 已提交
207
    def init_kernel_type(self):
K
Kexin Zhao 已提交
208 209 210 211 212 213 214 215 216 217
        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=1e-3)


218
class TestCUDNNCase2(TestCase1):
K
Kexin Zhao 已提交
219
    def init_kernel_type(self):
220
        self.use_cudnn = True
C
chengduoZH 已提交
221 222


K
Kexin Zhao 已提交
223
class TestFP16CUDNNCase2(TestCase1):
K
Kexin Zhao 已提交
224
    def init_kernel_type(self):
K
Kexin Zhao 已提交
225 226 227 228 229 230 231 232 233 234
        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=1e-3)


235
class TestCUDNNCase3(TestCase2):
K
Kexin Zhao 已提交
236
    def init_kernel_type(self):
237
        self.use_cudnn = True
C
chengduoZH 已提交
238 239


K
Kexin Zhao 已提交
240
class TestFP16CUDNNCase3(TestCase2):
K
Kexin Zhao 已提交
241
    def init_kernel_type(self):
K
Kexin Zhao 已提交
242 243 244 245 246 247 248 249 250 251
        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=1e-3)


252
class TestCUDNNCase4(TestCase3):
K
Kexin Zhao 已提交
253
    def init_kernel_type(self):
254
        self.use_cudnn = True
C
chengduoZH 已提交
255 256


K
Kexin Zhao 已提交
257
class TestFP16CUDNNCase4(TestCase3):
K
Kexin Zhao 已提交
258
    def init_kernel_type(self):
K
Kexin Zhao 已提交
259 260 261 262 263 264 265 266 267 268
        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=1e-3)


269
class TestCUDNNCase5(TestCase4):
K
Kexin Zhao 已提交
270
    def init_kernel_type(self):
271
        self.use_cudnn = True
C
chengduoZH 已提交
272

C
chengduoZH 已提交
273

K
Kexin Zhao 已提交
274
class TestFP16CUDNNCase5(TestCase4):
K
Kexin Zhao 已提交
275
    def init_kernel_type(self):
K
Kexin Zhao 已提交
276 277 278 279 280 281 282 283 284 285
        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=1e-3)


286
class TestCUDNNCase6(TestCase5):
K
Kexin Zhao 已提交
287
    def init_kernel_type(self):
288
        self.use_cudnn = True
C
chengduoZH 已提交
289

C
chengduoZH 已提交
290

K
Kexin Zhao 已提交
291
class TestFP16CUDNNCase6(TestCase5):
K
Kexin Zhao 已提交
292
    def init_kernel_type(self):
K
Kexin Zhao 已提交
293 294 295 296 297 298 299 300 301 302
        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=1e-3)


303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322
class TestCeilModeCase1(TestCUDNNCase1):
    def init_ceil_mode(self):
        self.ceil_mode = True


class TestCeilModeCase2(TestCUDNNCase2):
    def init_ceil_mode(self):
        self.ceil_mode = True


class TestCeilModeCase3(TestCase1):
    def init_ceil_mode(self):
        self.ceil_mode = True


class TestCeilModeCase4(TestCase2):
    def init_ceil_mode(self):
        self.ceil_mode = True


C
chengduoZH 已提交
323 324
if __name__ == '__main__':
    unittest.main()