dangqingqing
8 years ago
parent
3b1620167e
commit
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "paddle/platform/cudnn_helper.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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TEST(CudnnHelper, ScopedTensorDescriptor) {
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using paddle::platform::ScopedTensorDescriptor;
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using paddle::platform::DataLayout;
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ScopedTensorDescriptor tensor_desc;
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std::vector<int> shape = {2, 4, 6, 6};
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auto desc = tensor_desc.descriptor<float>(DataLayout::kNCHW, shape);
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cudnnDataType_t type;
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int nd;
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std::vector<int> dims(4);
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std::vector<int> strides(4);
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paddle::platform::dynload::cudnnGetTensorNdDescriptor(
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desc, 4, &type, &nd, dims.data(), strides.data());
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EXPECT_EQ(nd, 4);
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for (size_t i = 0; i < dims.size(); ++i) {
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EXPECT_EQ(dims[i], shape[i]);
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}
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EXPECT_EQ(strides[3], 1);
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EXPECT_EQ(strides[2], 6);
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EXPECT_EQ(strides[1], 36);
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EXPECT_EQ(strides[0], 144);
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}
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TEST(CudnnHelper, ScopedFilterDescriptor) {
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using paddle::platform::ScopedFilterDescriptor;
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using paddle::platform::DataLayout;
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ScopedFilterDescriptor filter_desc;
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std::vector<int> shape = {2, 3, 3};
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auto desc = filter_desc.descriptor<float>(DataLayout::kNCHW, shape);
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cudnnDataType_t type;
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int nd;
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cudnnTensorFormat_t format;
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std::vector<int> kernel(3);
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paddle::platform::dynload::cudnnGetFilterNdDescriptor(desc, 3, &type, &format,
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&nd, kernel.data());
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EXPECT_EQ(GetCudnnTensorFormat(DataLayout::kNCHW), format);
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EXPECT_EQ(nd, 3);
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for (size_t i = 0; i < shape.size(); ++i) {
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EXPECT_EQ(kernel[i], shape[i]);
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}
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}
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TEST(CudnnHelper, ScopedConvolutionDescriptor) {
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using paddle::platform::ScopedConvolutionDescriptor;
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ScopedConvolutionDescriptor conv_desc;
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std::vector<int> src_pads = {2, 2, 2};
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std::vector<int> src_strides = {1, 1, 1};
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std::vector<int> src_dilations = {1, 1, 1};
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auto desc = conv_desc.descriptor<float>(src_pads, src_strides, src_dilations);
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cudnnDataType_t type;
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cudnnConvolutionMode_t mode;
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int nd;
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std::vector<int> pads(3);
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std::vector<int> strides(3);
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std::vector<int> dilations(3);
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paddle::platform::dynload::cudnnGetConvolutionNdDescriptor(
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desc, 3, &nd, pads.data(), strides.data(), dilations.data(), &mode,
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&type);
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EXPECT_EQ(nd, 3);
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for (size_t i = 0; i < src_pads.size(); ++i) {
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EXPECT_EQ(pads[i], src_pads[i]);
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EXPECT_EQ(strides[i], src_strides[i]);
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EXPECT_EQ(dilations[i], src_dilations[i]);
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}
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EXPECT_EQ(mode, CUDNN_CROSS_CORRELATION);
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}
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TEST(CudnnHelper, ScopedPoolingDescriptor) {
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using paddle::platform::ScopedPoolingDescriptor;
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using paddle::platform::PoolingMode;
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ScopedPoolingDescriptor pool_desc;
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std::vector<int> src_kernel = {2, 2, 5};
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std::vector<int> src_pads = {1, 1, 2};
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std::vector<int> src_strides = {2, 2, 3};
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auto desc = pool_desc.descriptor(PoolingMode::kMaximum, src_kernel, src_pads,
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src_strides);
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cudnnPoolingMode_t mode;
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cudnnNanPropagation_t nan_t = CUDNN_PROPAGATE_NAN;
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int nd;
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std::vector<int> kernel(3);
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std::vector<int> pads(3);
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std::vector<int> strides(3);
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paddle::platform::dynload::cudnnGetPoolingNdDescriptor(
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desc, 3, &mode, &nan_t, &nd, kernel.data(), pads.data(), strides.data());
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EXPECT_EQ(nd, 3);
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for (size_t i = 0; i < src_pads.size(); ++i) {
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EXPECT_EQ(kernel[i], src_kernel[i]);
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EXPECT_EQ(pads[i], src_pads[i]);
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EXPECT_EQ(strides[i], src_strides[i]);
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}
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EXPECT_EQ(mode, CUDNN_POOLING_MAX);
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}
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@ -1,2 +1,2 @@
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cc_library(dynamic_loader SRCS dynamic_loader.cc DEPS glog gflags)
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nv_library(dynload_cuda SRCS cublas.cc cudnn.cc curand.cc)
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nv_library(dynload_cuda SRCS cublas.cc cudnn.cc curand.cc DEPS dynamic_loader)
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