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未验证 提交 0a96ec69 编写于 作者: Z Zeng Jinle 提交者： GitHub
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fix conv v7 workspace size limit error, test=develop (#17902)

上级 4d5f6937
隐藏空白更改
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Showing with 103 addition and 35 deletion
paddle/fluid/operators/conv_cudnn_op.cu.cc
浏览文件 @ 0a96ec69
......@@ -165,6 +165,7 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
// TODO(dangqingqing) simplify the following code by SearchAlgorithm in
// conv_cudnn_helper.h
bool has_got_workspace_size = false;
if ((!exhaustive_search) && (!half_float)) {
#if CUDNN_VERSION >= 7001
using perf_t = cudnnConvolutionFwdAlgoPerf_t;
......@@ -176,11 +177,29 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
cudnn_output_desc, kNUM_CUDNN_FWD_ALGS, &perf_count,
perf_results.get()));
algo = (perf_results.get())[best_algo_idx].algo;
#else
CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm(
// get workspace size able to allocate
CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardWorkspaceSize(
handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &algo));
cudnn_output_desc, algo, &workspace_size_in_bytes));
// NOTE(zjl): cudnnGetConvolutionForwardAlgorithm_v7 cannot limit
// workspace size. If the workspace size found by v7 exceeds the limit,
// we should fallback to non-v7 method to find another algorithm.
if (workspace_size_in_bytes > workspace_size_limit) {
VLOG(1) << "Fallback to non-v7 method to find conv algorithm becasue "
"the workspace size request("
<< workspace_size_in_bytes << ") exceeds the limit("
<< workspace_size_limit << ")";
#endif
CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm(
handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &algo));
#if CUDNN_VERSION >= 7001
} else {
has_got_workspace_size = true;
}
#endif
VLOG(3) << "cuDNN forward algo " << algo;
......@@ -219,10 +238,13 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
"cuDNN exhaustive search doesn't support half float.");
}
// get workspace size able to allocate
CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardWorkspaceSize(
handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
cudnn_output_desc, algo, &workspace_size_in_bytes));
if (!has_got_workspace_size) {
// get workspace size able to allocate
CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardWorkspaceSize(
handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
cudnn_output_desc, algo, &workspace_size_in_bytes));
}
// It is possible for float16 on Volta GPU to allocate more memory than
// the limit because the algo is overrided to use tensor core.
PADDLE_ENFORCE_LE(workspace_size_in_bytes, workspace_size_limit,
......@@ -366,6 +388,8 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
auto x_dims = framework::vectorize(input->dims());
auto f_dims = framework::vectorize(filter->dims());
auto handle = dev_ctx.cudnn_handle();
bool has_got_bwd_data_ws_size = false;
if (input_grad) {
T* input_grad_data = input_grad->mutable_data<T>(ctx.GetPlace());
if (exhaustive_search) {
......@@ -431,28 +455,49 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
CUDNN_CONVOLUTION_BWD_DATA_ALGO_FFT)) {
data_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1;
}
#else
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardDataAlgorithm(
handle, cudnn_filter_desc,
// dyDesc: Handle to the previously initialized input
// differential
// tensor descriptor.
cudnn_output_grad_desc, cudnn_conv_desc,
// dxDesc: Handle to the previously initialized output tensor
// descriptor.
cudnn_input_desc,
CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &data_algo));
platform::dynload::cudnnGetConvolutionBackwardDataWorkspaceSize(
handle, cudnn_filter_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_input_desc, data_algo, &tmp_size));
auto new_workspace_size = std::max(workspace_size_in_bytes, tmp_size);
if (new_workspace_size > workspace_size_limit) {
VLOG(1) << "Fallback to non-v7 method to find conv algorithm becasue "
"the workspace size request("
<< new_workspace_size << ") exceeds the limit("
<< workspace_size_limit << ")";
#endif
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardDataAlgorithm(
handle, cudnn_filter_desc,
// dyDesc: Handle to the previously initialized input
// differential
// tensor descriptor.
cudnn_output_grad_desc, cudnn_conv_desc,
// dxDesc: Handle to the previously initialized output tensor
// descriptor.
cudnn_input_desc,
CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &data_algo));
#if CUDNN_VERSION >= 7001
} else {
workspace_size_in_bytes = new_workspace_size;
has_got_bwd_data_ws_size = true;
}
#endif
}
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardDataWorkspaceSize(
handle, cudnn_filter_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_input_desc, data_algo, &tmp_size));
workspace_size_in_bytes = std::max(workspace_size_in_bytes, tmp_size);
if (!has_got_bwd_data_ws_size) {
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardDataWorkspaceSize(
handle, cudnn_filter_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_input_desc, data_algo, &tmp_size));
workspace_size_in_bytes = std::max(workspace_size_in_bytes, tmp_size);
}
}
bool has_got_bwd_filter_ws_size = false;
if (filter_grad) {
T* filter_grad_data = filter_grad->mutable_data<T>(ctx.GetPlace());
if (exhaustive_search) {
......@@ -495,22 +540,45 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
cudnn_conv_desc, cudnn_filter_desc, kNUM_CUDNN_BWD_FILTER_ALGS,
&perf_count, perf_results.get()));
filter_algo = (perf_results.get())[best_algo_idx].algo;
#else
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardFilterAlgorithm(
platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize(
handle, cudnn_input_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_filter_desc,
CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &filter_algo));
cudnn_conv_desc, cudnn_filter_desc, filter_algo, &tmp_size));
auto new_workspace_size = std::max(workspace_size_in_bytes, tmp_size);
if (new_workspace_size > workspace_size_limit) {
VLOG(1) << "Fallback to non-v7 method to find conv algorithm becasue "
"the workspace size request("
<< new_workspace_size << ") exceeds the limit("
<< workspace_size_limit << ")";
#endif
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardFilterAlgorithm(
handle, cudnn_input_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_filter_desc,
CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT,
workspace_size_limit, &filter_algo));
#if CUDNN_VERSION >= 7001
} else {
workspace_size_in_bytes = new_workspace_size;
has_got_bwd_filter_ws_size = true;
}
#endif
}
if (!has_got_bwd_filter_ws_size) {
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize(
handle, cudnn_input_desc, cudnn_output_grad_desc,
cudnn_conv_desc, cudnn_filter_desc, filter_algo, &tmp_size));
workspace_size_in_bytes = std::max(workspace_size_in_bytes, tmp_size);
}
CUDNN_ENFORCE(
platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize(
handle, cudnn_input_desc, cudnn_output_grad_desc, cudnn_conv_desc,
cudnn_filter_desc, filter_algo, &tmp_size));
workspace_size_in_bytes = std::max(workspace_size_in_bytes, tmp_size);
}
PADDLE_ENFORCE_LE(workspace_size_in_bytes, workspace_size_limit,
"workspace_size to be allocated exceeds the limit");
// ------------------- cudnn conv workspace ---------------------
if (!cudnn_workspace_ptr) {
cudnn_workspace =
......
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