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cudnn_convolution.cpp
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cudnn_convolution.cpp
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/**
* The #include<ATen/cudnn/*.h> needs guards as pointed in
* https://github.com/pytorch/pytorch/tree/master/aten/src/ATen/cudnn
*/
#include <ATen/cuda/CUDAConfig.h> // for the definition of AT_CUDNN_ENABLED
#if AT_CUDNN_ENABLED()
#include <cudnn.h>
#include <torch/extension.h>
#include <ATen/cudnn/Handle.h> // for getCudnnHandle
#include "cudnn_utils.h"
/*
PyTorch extension enabling direct access to the following cuDNN-accelerated C++ functions
that are included in PyTorch:
- cudnn_convolution
- cudnn_convolution_backward_weight
- cudnn_convolution_backward_input
The functions defined here can be called from Python in replacement of
torch.nn.conv2d, torch.nn.grad.conv2d_weight and torch.nn.grad.conv2d_input,
and run significantly faster. See 'example.py' for how these functions
are called.
Adapted from code posted by goldsborough/conv.cu:
https://gist.github.com/eduardo4jesus/33ef6d8696e8af70a3046e9f364a65f8#file-conv-cu
*/
std::ostream &cout_unit(std::ostream &out, const size_t &nbytes) {
if ((nbytes / (1u<<30)) > 1)
out << nbytes/(1u<<30) << " GB";
else if ((nbytes / (1u<<20)) > 1)
out << nbytes/(1u<<20) << " MB";
else if ((nbytes / (1u<<10)) > 1)
out << nbytes/(1u<<10) << " KB";
out << " (" << nbytes << " Bytes)";
return out;
}
at::Tensor convolution(const int fwdAlgo,
const at::Tensor &input, const at::Tensor &weight, const at::Tensor &output,
c10::ArrayRef<int64_t> stride, c10::ArrayRef<int64_t> padding,
c10::ArrayRef<int64_t> dilation, int64_t groups, bool verbose)
{
const cudnnHandle_t cudnn = at::native::getCudnnHandle();
/*****************************************************************************
* 1. Initializing Descriptors
****************************************************************************/
cudnnDescriptors_t desc;
initialize_descriptors(input, weight, output, stride, padding, dilation, desc);
/*****************************************************************************
* 2. Setting FWD Convolution Algo
****************************************************************************/
cudnnConvolutionFwdAlgoPerf_t convolution_algorithm[CUDNN_CONVOLUTION_FWD_ALGO_COUNT];
int returnedAlgoCount;
if (fwdAlgo == -1)
{
if (verbose)
std::cout << "Trying all" << std::endl;
checkCUDNN(
cudnnFindConvolutionForwardAlgorithm(/*handle*/ cudnn,
/*xDesc*/ desc.input,
/*wDesc*/ desc.weight,
/*convDesc*/ desc.convolution,
/*yDesc*/ desc.output,
/*requestedAlgoCount*/ CUDNN_CONVOLUTION_FWD_ALGO_COUNT,
/*returnedAlgoCount*/ &returnedAlgoCount,
/*perfResults*/ convolution_algorithm));
if (verbose)
for (int i = 0; i < returnedAlgoCount; i++)
std::cout << convolution_algorithm[i] << std::endl;
}
else
{
convolution_algorithm[0].algo = static_cast<cudnnConvolutionFwdAlgo_t>(fwdAlgo);
convolution_algorithm[0].status = static_cast<cudnnStatus_t>(0);
convolution_algorithm[0].time = -1;
convolution_algorithm[0].memory = 0;
convolution_algorithm[0].determinism = static_cast<cudnnDeterminism_t>(-1);
convolution_algorithm[0].mathType = static_cast<cudnnMathType_t>(0);
if (verbose)
{
std::cout << "Attempt with defined Algo:" << std::endl;
std::cout << convolution_algorithm[0] << std::endl;
}
}
/*****************************************************************************
* 3. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose)
std::cout << "Allocating Workspace" << std::endl;
size_t workspace_bytes{0};
checkCUDNN(cudnnGetConvolutionForwardWorkspaceSize(cudnn,
/*xDesc*/ desc.input,
/*wDesc*/ desc.weight,
/*convDesc*/ desc.convolution,
/*yDesc*/ desc.output,
/*algo*/ convolution_algorithm[0].algo,
/*sizeInBytes*/ &workspace_bytes));
/*****************************************************************************
* 4. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose) {
std::cout << "Workspace size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
void *d_workspace{nullptr};
cudaMalloc(&d_workspace, workspace_bytes);
if (verbose) {
std::cout << "Allocated size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
/*****************************************************************************
* 5. Call CuDNN Convolution
****************************************************************************/
// cudaEvent_t start, stop;
// cudaEventCreate(&start);
// cudaEventCreate(&stop);
// cudaEventRecord(start);
const float alpha = 1.0f, beta = 0.0f;
checkCUDNN(cudnnConvolutionForward(cudnn,
/*alpha*/ &alpha,
/*xDesc*/ desc.input,
/*x*/ input.data_ptr(),
/*wDesc*/ desc.weight,
/*w*/ weight.data_ptr(),
/*convDesc*/ desc.convolution,
/*algo*/ convolution_algorithm[0].algo,
/*workSpace*/ d_workspace,
/*workSpaceSizeInBytes*/ workspace_bytes,
/*beta*/ &beta,
/*yDesc*/ desc.output,
/*y*/ output.data_ptr()));
// cudaEventRecord(stop);
// cudaEventSynchronize(stop);
// float milliseconds{0};
// cudaEventElapsedTime(&milliseconds, start, stop);
// if (verbose)
// std::cout << "Elapsed Time: " << milliseconds << " ms" << std::endl;
/*****************************************************************************
* 5. Freeing variables
****************************************************************************/
cudaFree(d_workspace);
return output;
}
at::Tensor convolution_backward_weight(const int bwdFilterAlgo,
const at::Tensor &input, const at::Tensor &weight, const at::Tensor &output,
c10::ArrayRef<int64_t> stride, c10::ArrayRef<int64_t> padding,
c10::ArrayRef<int64_t> dilation, int64_t groups, bool verbose)
{
const cudnnHandle_t cudnn = at::native::getCudnnHandle();
/*****************************************************************************
* 1. Initializing Descriptors
****************************************************************************/
cudnnDescriptors_t desc;
initialize_descriptors(input, weight, output, stride, padding, dilation, desc);
/*****************************************************************************
* 2. Setting BWD Convolution Filter Algo
****************************************************************************/
cudnnConvolutionBwdFilterAlgoPerf_t convolution_algorithm[CUDNN_CONVOLUTION_BWD_FILTER_ALGO_COUNT];
int returnedAlgoCount;
if (bwdFilterAlgo == -1)
{
if (verbose)
std::cout << "Trying all" << std::endl;
checkCUDNN(
cudnnFindConvolutionBackwardFilterAlgorithm(/*handle*/ cudnn,
/*xDesc*/ desc.input,
/*dyDesc*/ desc.output,
/*convDesc*/ desc.convolution,
/*dwDesc*/ desc.weight,
/*requestedAlgoCount*/ CUDNN_CONVOLUTION_BWD_FILTER_ALGO_COUNT,
/*returnedAlgoCount*/ &returnedAlgoCount,
/*perfResults*/ convolution_algorithm));
if (verbose)
for (int i = 0; i < returnedAlgoCount; i++)
std::cout << convolution_algorithm[i] << std::endl;
}
else
{
convolution_algorithm[0].algo = static_cast<cudnnConvolutionBwdFilterAlgo_t>(bwdFilterAlgo);
convolution_algorithm[0].status = static_cast<cudnnStatus_t>(0);
convolution_algorithm[0].time = -1;
convolution_algorithm[0].memory = 0;
convolution_algorithm[0].determinism = static_cast<cudnnDeterminism_t>(-1);
convolution_algorithm[0].mathType = static_cast<cudnnMathType_t>(0);
if (verbose)
{
std::cout << "Attempt with defined Algo:" << std::endl;
std::cout << convolution_algorithm[0] << std::endl;
}
}
/*****************************************************************************
* 3. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose)
std::cout << "Allocating Workspace" << std::endl;
size_t workspace_bytes{0};
checkCUDNN(cudnnGetConvolutionBackwardFilterWorkspaceSize(cudnn,
/*xDesc*/ desc.input,
/*dyDesc*/ desc.output,
/*convDesc*/ desc.convolution,
/*dwDesc*/ desc.weight,
/*algo*/ convolution_algorithm[0].algo,
/*sizeInBytes*/ &workspace_bytes));
/*****************************************************************************
* 4. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose) {
std::cout << "Workspace size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
void *d_workspace{nullptr};
cudaMalloc(&d_workspace, workspace_bytes);
if (verbose) {
std::cout << "Allocated size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
/*****************************************************************************
* Call CuDNN Convolution
****************************************************************************/
// cudaEvent_t start, stop;
// cudaEventCreate(&start);
// cudaEventCreate(&stop);
// cudaEventRecord(start);
const float alpha = 1.0f, beta = 0.0f;
checkCUDNN(cudnnConvolutionBackwardFilter(cudnn,
/*alpha*/ &alpha,
/*xDesc*/ desc.input,
/*x*/ input.data_ptr(),
/*dyDesc*/ desc.output,
/*dy*/ output.data_ptr(),
/*convDesc*/ desc.convolution,
/*algo*/ convolution_algorithm[0].algo,
/*workSpace*/ d_workspace,
/*workSpaceSizeInBytes*/ workspace_bytes,
/*beta*/ &beta,
/*dwDesc*/ desc.weight,
/*dw*/ weight.data_ptr()
));
// cudaEventRecord(stop);
// cudaEventSynchronize(stop);
// float milliseconds{0};
// cudaEventElapsedTime(&milliseconds, start, stop);
// if (verbose)
// std::cout << "Elapsed Time: " << milliseconds << " ms" << std::endl;
/*****************************************************************************
* 5. Freeing variables
****************************************************************************/
cudaFree(d_workspace);
return output;
}
at::Tensor convolution_backward_input(const int bwdDataAlgo,
const at::Tensor &input, const at::Tensor &weight, const at::Tensor &output,
c10::ArrayRef<int64_t> stride, c10::ArrayRef<int64_t> padding,
c10::ArrayRef<int64_t> dilation, int64_t groups, bool verbose)
{
const cudnnHandle_t cudnn = at::native::getCudnnHandle();
/*****************************************************************************
* 1. Initializing Descriptors
****************************************************************************/
cudnnDescriptors_t desc;
initialize_descriptors(input, weight, output, stride, padding, dilation, desc);
/*****************************************************************************
* 2. Setting BWD Convolution Data Algo
****************************************************************************/
cudnnConvolutionBwdDataAlgoPerf_t convolution_algorithm[CUDNN_CONVOLUTION_BWD_DATA_ALGO_COUNT];
int returnedAlgoCount;
/**
* TODO: I frequently get segmentation fault when finding the convolution
* algorithms. I am not sure how to fix it.
*/
if (bwdDataAlgo == -1)
{
if (verbose)
std::cout << "Trying all" << std::endl;
checkCUDNN(
cudnnFindConvolutionBackwardDataAlgorithm(/*handle*/ cudnn,
/*wDesc*/ desc.weight,
/*dyDesc*/ desc.output,
/*convDesc*/ desc.convolution,
/*dxDesc*/ desc.input,
/*requestedAlgoCount*/ CUDNN_CONVOLUTION_BWD_DATA_ALGO_COUNT,
/*returnedAlgoCount*/ &returnedAlgoCount,
/*perfResults*/ convolution_algorithm));
if (verbose)
for (int i = 0; i < returnedAlgoCount; i++)
std::cout << convolution_algorithm[i] << std::endl;
}
else
{
convolution_algorithm[0].algo = static_cast<cudnnConvolutionBwdDataAlgo_t>(bwdDataAlgo);
convolution_algorithm[0].status = static_cast<cudnnStatus_t>(0);
convolution_algorithm[0].time = -1;
convolution_algorithm[0].memory = 0;
convolution_algorithm[0].determinism = static_cast<cudnnDeterminism_t>(-1);
convolution_algorithm[0].mathType = static_cast<cudnnMathType_t>(0);
if (verbose)
{
std::cout << "Attempt with defined Algo:" << std::endl;
std::cout << convolution_algorithm[0] << std::endl;
}
}
/*****************************************************************************
* 3. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose)
std::cout << "Allocating Workspace" << std::endl;
size_t workspace_bytes{0};
checkCUDNN(cudnnGetConvolutionBackwardDataWorkspaceSize(cudnn,
/*wDesc*/ desc.weight,
/*dyDesc*/ desc.output,
/*convDesc*/ desc.convolution,
/*dxDesc*/ desc.input,
/*algo*/ convolution_algorithm[0].algo,
/*sizeInBytes*/ &workspace_bytes));
/*****************************************************************************
* 4. Get and Allocate Memory for Workspace
****************************************************************************/
if (verbose) {
std::cout << "Workspace size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
void *d_workspace{nullptr};
cudaMalloc(&d_workspace, workspace_bytes);
if (verbose) {
std::cout << "Allocated size: ";
cout_unit(std::cout, workspace_bytes) << std::endl;
}
/*****************************************************************************
* 5. Call CuDNN Convolution
****************************************************************************/
// cudaEvent_t start, stop;
// cudaEventCreate(&start);
// cudaEventCreate(&stop);
// cudaEventRecord(start);
const float alpha = 1.0f, beta = 0.0f;
checkCUDNN(cudnnConvolutionBackwardData(cudnn,
/*alpha*/ &alpha,
/*wDesc*/ desc.weight,
/*w*/ weight.data_ptr(),
/*dyDesc*/ desc.output,
/*dy*/ output.data_ptr(),
/*convDesc*/ desc.convolution,
/*algo*/ convolution_algorithm[0].algo,
/*workSpace*/ d_workspace,
/*workSpaceSizeInBytes*/ workspace_bytes,
/*beta*/ &beta,
/*xDesc*/ desc.input,
/*x*/ input.data_ptr()));
// cudaEventRecord(stop);
// cudaEventSynchronize(stop);
// float milliseconds{0};
// cudaEventElapsedTime(&milliseconds, start, stop);
// if (verbose)
// std::cout << "Elapsed Time: " << milliseconds << " ms" << std::endl;
/*****************************************************************************
* 5. Freeing variables
****************************************************************************/
cudaFree(d_workspace);
return output;
}
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
{
m.def("convolution", &convolution, "convolution");
m.def("convolution_backward_weight", &convolution_backward_weight, "convolution backward weight");
m.def("convolution_backward_input", &convolution_backward_input, "convolution backward input");
}
#endif