-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
14 changed files
with
1,641 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,34 @@ | ||
cmake_minimum_required (VERSION 2.6) | ||
project (cudnn-training) | ||
|
||
find_package(CUDA 6.5 REQUIRED) | ||
|
||
|
||
if (CMAKE_BUILD_TYPE STREQUAL "Debug") | ||
message("Debug mode") | ||
set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS};-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_50,code=compute_50;-std=c++11;-g;-lineinfo;-Xcompiler;-ggdb) | ||
else() | ||
set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS};-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_50,code=compute_50;-std=c++11;-O3;-DNDEBUG;-Xcompiler;-DNDEBUG) | ||
endif() | ||
|
||
set(CUDA_PROPAGATE_HOST_FLAGS OFF) | ||
|
||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11") | ||
|
||
if(USE_GFLAGS) | ||
add_definitions(-DUSE_GFLAGS) | ||
endif() | ||
|
||
include_directories($ENV{CUDNN_PATH} $ENV{CUDNN_PATH}/include) | ||
link_directories($ENV{CUDNN_PATH} $ENV{CUDNN_PATH}/lib $ENV{CUDNN_PATH}/lib64) | ||
|
||
cuda_add_executable(trainlenet lenet.cu readubyte.cpp) | ||
cuda_add_cublas_to_target(trainlenet) | ||
|
||
if(USE_GFLAGS) | ||
target_link_libraries(trainlenet gflags cudnn) | ||
else() | ||
target_link_libraries(trainlenet cudnn) | ||
endif() | ||
|
||
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,17 @@ | ||
CXX := nvcc | ||
TARGET := cudnn_conv_test | ||
CUDNN_PATH := cudnn | ||
HEADERS := -I $(CUDNN_PATH)/include | ||
LIBS := -L $(CUDNN_PATH)/lib64 -L/usr/local/lib | ||
CXXFLAGS := -gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_61,code=sm_61 -std=c++11 -O2 | ||
|
||
all: conv | ||
|
||
conv: $(TARGET).cu | ||
$(CXX) $(CXXFLAGS) $(HEADERS) $(LIBS) $(TARGET).cu -o $(TARGET) \ | ||
-lcudnn -lopencv_imgcodecs -lopencv_imgproc -lopencv_core | ||
|
||
.phony: clean | ||
|
||
clean: | ||
rm $(TARGET) || echo -n "" |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file not shown.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,226 @@ | ||
#include <cudnn.h> | ||
#include <cassert> | ||
#include <cstdlib> | ||
#include <iostream> | ||
#include <opencv2/opencv.hpp> | ||
|
||
#define checkCUDNN(expression) \ | ||
{ \ | ||
cudnnStatus_t status = (expression); \ | ||
if (status != CUDNN_STATUS_SUCCESS) { \ | ||
std::cerr << "Error on line " << __LINE__ << ": " \ | ||
<< cudnnGetErrorString(status) << std::endl; \ | ||
std::exit(EXIT_FAILURE); \ | ||
} \ | ||
} | ||
|
||
cv::Mat load_image(const char* image_path) { | ||
cv::Mat image = cv::imread(image_path, CV_LOAD_IMAGE_COLOR); | ||
image.convertTo(image, CV_32FC3); | ||
cv::normalize(image, image, 0, 1, cv::NORM_MINMAX); | ||
std::cerr << "Input Image: " << image.rows << " x " << image.cols << " x " | ||
<< image.channels() << std::endl; | ||
return image; | ||
} | ||
|
||
void save_image(const char* output_filename, | ||
float* buffer, | ||
int height, | ||
int width) { | ||
cv::Mat output_image(height, width, CV_32FC3, buffer); | ||
// Make negative values zero. | ||
cv::threshold(output_image, | ||
output_image, | ||
/*threshold=*/0, | ||
/*maxval=*/0, | ||
cv::THRESH_TOZERO); | ||
cv::normalize(output_image, output_image, 0.0, 255.0, cv::NORM_MINMAX); | ||
output_image.convertTo(output_image, CV_8UC3); | ||
cv::imwrite(output_filename, output_image); | ||
std::cerr << "Wrote output to " << output_filename << std::endl; | ||
} | ||
|
||
int main(int argc, const char* argv[]) { | ||
if (argc < 2) { | ||
std::cerr << "usage: conv <image> [gpu=0] [sigmoid=0]" << std::endl; | ||
std::exit(EXIT_FAILURE); | ||
} | ||
|
||
int gpu_id = (argc > 2) ? std::atoi(argv[2]) : 0; | ||
std::cerr << "GPU: " << gpu_id << std::endl; | ||
|
||
bool with_sigmoid = (argc > 3) ? std::atoi(argv[3]) : 0; | ||
std::cerr << "With sigmoid: " << std::boolalpha << with_sigmoid << std::endl; | ||
|
||
cv::Mat image = load_image(argv[1]); | ||
|
||
cudaSetDevice(gpu_id); | ||
|
||
cudnnHandle_t cudnn; | ||
cudnnCreate(&cudnn); | ||
|
||
cudnnTensorDescriptor_t input_descriptor; | ||
checkCUDNN(cudnnCreateTensorDescriptor(&input_descriptor)); | ||
checkCUDNN(cudnnSetTensor4dDescriptor(input_descriptor, | ||
/*format=*/CUDNN_TENSOR_NHWC, | ||
/*dataType=*/CUDNN_DATA_FLOAT, | ||
/*batch_size=*/1, | ||
/*channels=*/3, | ||
/*image_height=*/image.rows, | ||
/*image_width=*/image.cols)); | ||
|
||
cudnnFilterDescriptor_t kernel_descriptor; | ||
checkCUDNN(cudnnCreateFilterDescriptor(&kernel_descriptor)); | ||
checkCUDNN(cudnnSetFilter4dDescriptor(kernel_descriptor, | ||
/*dataType=*/CUDNN_DATA_FLOAT, | ||
/*format=*/CUDNN_TENSOR_NCHW, | ||
/*out_channels=*/3, | ||
/*in_channels=*/3, | ||
/*kernel_height=*/3, | ||
/*kernel_width=*/3)); | ||
|
||
cudnnConvolutionDescriptor_t convolution_descriptor; | ||
checkCUDNN(cudnnCreateConvolutionDescriptor(&convolution_descriptor)); | ||
checkCUDNN(cudnnSetConvolution2dDescriptor(convolution_descriptor, | ||
/*pad_height=*/1, | ||
/*pad_width=*/1, | ||
/*vertical_stride=*/1, | ||
/*horizontal_stride=*/1, | ||
/*dilation_height=*/1, | ||
/*dilation_width=*/1, | ||
/*mode=*/CUDNN_CROSS_CORRELATION, | ||
/*computeType=*/CUDNN_DATA_FLOAT)); | ||
|
||
int batch_size{0}, channels{0}, height{0}, width{0}; | ||
checkCUDNN(cudnnGetConvolution2dForwardOutputDim(convolution_descriptor, | ||
input_descriptor, | ||
kernel_descriptor, | ||
&batch_size, | ||
&channels, | ||
&height, | ||
&width)); | ||
|
||
std::cerr << "Output Image: " << height << " x " << width << " x " << channels | ||
<< std::endl; | ||
|
||
cudnnTensorDescriptor_t output_descriptor; | ||
checkCUDNN(cudnnCreateTensorDescriptor(&output_descriptor)); | ||
checkCUDNN(cudnnSetTensor4dDescriptor(output_descriptor, | ||
/*format=*/CUDNN_TENSOR_NHWC, | ||
/*dataType=*/CUDNN_DATA_FLOAT, | ||
/*batch_size=*/1, | ||
/*channels=*/3, | ||
/*image_height=*/image.rows, | ||
/*image_width=*/image.cols)); | ||
|
||
cudnnConvolutionFwdAlgo_t convolution_algorithm; | ||
checkCUDNN( | ||
cudnnGetConvolutionForwardAlgorithm(cudnn, | ||
input_descriptor, | ||
kernel_descriptor, | ||
convolution_descriptor, | ||
output_descriptor, | ||
CUDNN_CONVOLUTION_FWD_PREFER_FASTEST, | ||
/*memoryLimitInBytes=*/0, | ||
&convolution_algorithm)); | ||
|
||
size_t workspace_bytes{0}; | ||
checkCUDNN(cudnnGetConvolutionForwardWorkspaceSize(cudnn, | ||
input_descriptor, | ||
kernel_descriptor, | ||
convolution_descriptor, | ||
output_descriptor, | ||
convolution_algorithm, | ||
&workspace_bytes)); | ||
std::cerr << "Workspace size: " << (workspace_bytes / 1048576.0) << "MB" | ||
<< std::endl; | ||
assert(workspace_bytes > 0); | ||
|
||
void* d_workspace{nullptr}; | ||
cudaMalloc(&d_workspace, workspace_bytes); | ||
|
||
int image_bytes = batch_size * channels * height * width * sizeof(float); | ||
|
||
float* d_input{nullptr}; | ||
cudaMalloc(&d_input, image_bytes); | ||
cudaMemcpy(d_input, image.ptr<float>(0), image_bytes, cudaMemcpyHostToDevice); | ||
|
||
float* d_output{nullptr}; | ||
cudaMalloc(&d_output, image_bytes); | ||
cudaMemset(d_output, 0, image_bytes); | ||
|
||
// clang-format off | ||
const float kernel_template[3][3] = { | ||
{1, 1, 1}, | ||
{1, -8, 1}, | ||
{1, 1, 1} | ||
}; | ||
// clang-format on | ||
|
||
float h_kernel[3][3][3][3]; | ||
for (int kernel = 0; kernel < 3; ++kernel) { | ||
for (int channel = 0; channel < 3; ++channel) { | ||
for (int row = 0; row < 3; ++row) { | ||
for (int column = 0; column < 3; ++column) { | ||
h_kernel[kernel][channel][row][column] = kernel_template[row][column]; | ||
} | ||
} | ||
} | ||
} | ||
|
||
float* d_kernel{nullptr}; | ||
cudaMalloc(&d_kernel, sizeof(h_kernel)); | ||
cudaMemcpy(d_kernel, h_kernel, sizeof(h_kernel), cudaMemcpyHostToDevice); | ||
|
||
const float alpha = 1.0f, beta = 0.0f; | ||
|
||
checkCUDNN(cudnnConvolutionForward(cudnn, | ||
&alpha, | ||
input_descriptor, | ||
d_input, | ||
kernel_descriptor, | ||
d_kernel, | ||
convolution_descriptor, | ||
convolution_algorithm, | ||
d_workspace, | ||
workspace_bytes, | ||
&beta, | ||
output_descriptor, | ||
d_output)); | ||
|
||
if (with_sigmoid) { | ||
cudnnActivationDescriptor_t activation_descriptor; | ||
checkCUDNN(cudnnCreateActivationDescriptor(&activation_descriptor)); | ||
checkCUDNN(cudnnSetActivationDescriptor(activation_descriptor, | ||
CUDNN_ACTIVATION_SIGMOID, | ||
CUDNN_PROPAGATE_NAN, | ||
/*relu_coef=*/0)); | ||
checkCUDNN(cudnnActivationForward(cudnn, | ||
activation_descriptor, | ||
&alpha, | ||
output_descriptor, | ||
d_output, | ||
&beta, | ||
output_descriptor, | ||
d_output)); | ||
cudnnDestroyActivationDescriptor(activation_descriptor); | ||
} | ||
|
||
float* h_output = new float[image_bytes]; | ||
cudaMemcpy(h_output, d_output, image_bytes, cudaMemcpyDeviceToHost); | ||
|
||
save_image("cudnn-out.png", h_output, height, width); | ||
|
||
delete[] h_output; | ||
cudaFree(d_kernel); | ||
cudaFree(d_input); | ||
cudaFree(d_output); | ||
cudaFree(d_workspace); | ||
|
||
cudnnDestroyTensorDescriptor(input_descriptor); | ||
cudnnDestroyTensorDescriptor(output_descriptor); | ||
cudnnDestroyFilterDescriptor(kernel_descriptor); | ||
cudnnDestroyConvolutionDescriptor(convolution_descriptor); | ||
|
||
cudnnDestroy(cudnn); | ||
} |
Oops, something went wrong.