#include "./algo.h"
#include "src/cuda/conv_bias/helper.h"
#include "src/cuda/convolution/helper.h"
#include "src/cuda/cudnn_wrapper.h"
#include "src/cuda/utils.h"
using namespace megdnn;
using namespace cuda;
using namespace convolution;
bool ConvolutionBackwardDataImpl::AlgoCUDNN::is_available(const SizeArgs& args) const {
if (args.filter_meta.format != Param::Format::NCHW &&
args.filter_meta.format != Param::Format::NHWC) {
if (!args.grad_layout->is_contiguous() || !args.diff_layout->is_contiguous()) {
return false;
}
}
CUDNNBwdDataDescs D;
TensorLayout bias_layout, z_layout;
conv_bias::CanonizedFilterMeta meta;
meta.copy_from(args.filter_meta);
conv_bias::BiasForwardSizeArgs bias_args{
args.handle, args.grad_layout,
args.filter_layout, &bias_layout,
&z_layout, meta,
args.diff_layout, param::ConvBias::NonlineMode::IDENTITY,
};
if (!conv_bias::is_cudnn_supported(bias_args))
return false;
args.init_desc(D);
size_t workspace_size;
auto status = cudnnGetConvolutionBackwardDataWorkspaceSize(
args.handle->cudnn_handle(), D.filter_desc.desc, D.diff_desc.desc,
D.conv_desc.desc, D.grad_desc.desc, m_cudnn_enum, &workspace_size);
return status == CUDNN_STATUS_SUCCESS;
}
size_t ConvolutionBackwardDataImpl::AlgoCUDNN::get_workspace_in_bytes(
const SizeArgs& args) const {
CUDNNBwdDataDescs D;
args.init_desc(D);
size_t workspace_size;
auto status = cudnnGetConvolutionBackwardDataWorkspaceSize(
args.handle->cudnn_handle(), D.filter_desc.desc, D.diff_desc.desc,
D.conv_desc.desc, D.grad_desc.desc, m_cudnn_enum, &workspace_size);
megdnn_assert(
status == CUDNN_STATUS_SUCCESS,
"conv bwd_data get workspace failed: %s; info: %s",
cudnnGetErrorString(status), args.to_string().c_str());
return workspace_size;
}
void ConvolutionBackwardDataImpl::AlgoCUDNN::exec(const ExecArgs& args) const {
CUDNNBwdDataDescs D;
args.init_desc(D);
float alpha = 1.0f, beta = 0.0f;
auto status = cudnnConvolutionBackwardData(
args.handle->cudnn_handle(), &alpha, D.filter_desc.desc,
args.filter_tensor->raw_ptr(), D.diff_desc.desc,
args.diff_tensor->raw_ptr(), D.conv_desc.desc, m_cudnn_enum,
args.workspace.raw_ptr, args.workspace.size, &beta, D.grad_desc.desc,
args.grad_tensor->raw_ptr());
megdnn_assert(
status == CUDNN_STATUS_SUCCESS, "conv bwd_data failed: %s; info: %s",
cudnnGetErrorString(status), args.to_string().c_str());
}
void ConvolutionBackwardDataImpl::AlgoPack::fill_cudnn_algos() {
for (auto&& algo : CudnnAlgoPack::conv_bwd_data_algos()) {
cudnn.push_back(algo.first);
}
}