You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
121 lines
3.9 KiB
121 lines
3.9 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
|
|
|
|
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. */
|
|
|
|
#include "paddle/platform/cudnn_helper.h"
|
|
#include <gtest/gtest.h>
|
|
|
|
TEST(CudnnHelper, ScopedTensorDescriptor) {
|
|
using paddle::platform::ScopedTensorDescriptor;
|
|
using paddle::platform::DataLayout;
|
|
|
|
ScopedTensorDescriptor tensor_desc;
|
|
std::vector<int> shape = {2, 4, 6, 6};
|
|
auto desc = tensor_desc.descriptor<float>(DataLayout::kNCHW, shape);
|
|
|
|
cudnnDataType_t type;
|
|
int nd;
|
|
std::vector<int> dims(4);
|
|
std::vector<int> strides(4);
|
|
paddle::platform::dynload::cudnnGetTensorNdDescriptor(
|
|
desc, 4, &type, &nd, dims.data(), strides.data());
|
|
|
|
EXPECT_EQ(nd, 4);
|
|
for (size_t i = 0; i < dims.size(); ++i) {
|
|
EXPECT_EQ(dims[i], shape[i]);
|
|
}
|
|
EXPECT_EQ(strides[3], 1);
|
|
EXPECT_EQ(strides[2], 6);
|
|
EXPECT_EQ(strides[1], 36);
|
|
EXPECT_EQ(strides[0], 144);
|
|
}
|
|
|
|
TEST(CudnnHelper, ScopedFilterDescriptor) {
|
|
using paddle::platform::ScopedFilterDescriptor;
|
|
using paddle::platform::DataLayout;
|
|
|
|
ScopedFilterDescriptor filter_desc;
|
|
std::vector<int> shape = {2, 3, 3};
|
|
auto desc = filter_desc.descriptor<float>(DataLayout::kNCHW, shape);
|
|
|
|
cudnnDataType_t type;
|
|
int nd;
|
|
cudnnTensorFormat_t format;
|
|
std::vector<int> kernel(3);
|
|
paddle::platform::dynload::cudnnGetFilterNdDescriptor(desc, 3, &type, &format,
|
|
&nd, kernel.data());
|
|
|
|
EXPECT_EQ(GetCudnnTensorFormat(DataLayout::kNCHW), format);
|
|
EXPECT_EQ(nd, 3);
|
|
for (size_t i = 0; i < shape.size(); ++i) {
|
|
EXPECT_EQ(kernel[i], shape[i]);
|
|
}
|
|
}
|
|
|
|
TEST(CudnnHelper, ScopedConvolutionDescriptor) {
|
|
using paddle::platform::ScopedConvolutionDescriptor;
|
|
|
|
ScopedConvolutionDescriptor conv_desc;
|
|
std::vector<int> src_pads = {2, 2, 2};
|
|
std::vector<int> src_strides = {1, 1, 1};
|
|
std::vector<int> src_dilations = {1, 1, 1};
|
|
auto desc = conv_desc.descriptor<float>(src_pads, src_strides, src_dilations);
|
|
|
|
cudnnDataType_t type;
|
|
cudnnConvolutionMode_t mode;
|
|
int nd;
|
|
std::vector<int> pads(3);
|
|
std::vector<int> strides(3);
|
|
std::vector<int> dilations(3);
|
|
paddle::platform::dynload::cudnnGetConvolutionNdDescriptor(
|
|
desc, 3, &nd, pads.data(), strides.data(), dilations.data(), &mode,
|
|
&type);
|
|
|
|
EXPECT_EQ(nd, 3);
|
|
for (size_t i = 0; i < src_pads.size(); ++i) {
|
|
EXPECT_EQ(pads[i], src_pads[i]);
|
|
EXPECT_EQ(strides[i], src_strides[i]);
|
|
EXPECT_EQ(dilations[i], src_dilations[i]);
|
|
}
|
|
EXPECT_EQ(mode, CUDNN_CROSS_CORRELATION);
|
|
}
|
|
|
|
TEST(CudnnHelper, ScopedPoolingDescriptor) {
|
|
using paddle::platform::ScopedPoolingDescriptor;
|
|
using paddle::platform::PoolingMode;
|
|
|
|
ScopedPoolingDescriptor pool_desc;
|
|
std::vector<int> src_kernel = {2, 2, 5};
|
|
std::vector<int> src_pads = {1, 1, 2};
|
|
std::vector<int> src_strides = {2, 2, 3};
|
|
auto desc = pool_desc.descriptor(PoolingMode::kMaximum, src_kernel, src_pads,
|
|
src_strides);
|
|
|
|
cudnnPoolingMode_t mode;
|
|
cudnnNanPropagation_t nan_t = CUDNN_PROPAGATE_NAN;
|
|
int nd;
|
|
std::vector<int> kernel(3);
|
|
std::vector<int> pads(3);
|
|
std::vector<int> strides(3);
|
|
paddle::platform::dynload::cudnnGetPoolingNdDescriptor(
|
|
desc, 3, &mode, &nan_t, &nd, kernel.data(), pads.data(), strides.data());
|
|
|
|
EXPECT_EQ(nd, 3);
|
|
for (size_t i = 0; i < src_pads.size(); ++i) {
|
|
EXPECT_EQ(kernel[i], src_kernel[i]);
|
|
EXPECT_EQ(pads[i], src_pads[i]);
|
|
EXPECT_EQ(strides[i], src_strides[i]);
|
|
}
|
|
EXPECT_EQ(mode, CUDNN_POOLING_MAX);
|
|
}
|