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Made tensor_conv hold references to the cuda_data_void_ptr work buffers in the 

member area of the class.  This way, we avoid a potential error where the
buffers are reallocated while cuDNN is still using them in the background.
This commit is contained in:
Davis King 2017-07-22 07:50:52 -04:00
parent 863702f059
commit 1f5335c1ad
2 changed files with 31 additions and 3 deletions
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31
dlib/dnn/cudnn_dlibapi.cpp
View File

@ -795,6 +795,9 @@ namespace dlib
backward_data_workspace_size_in_bytes = 0;
backward_filters_workspace_size_in_bytes = 0;
forward_workspace.reset();
backward_data_workspace.reset();
backward_filters_workspace.reset();
workspace.reset();
}
@ -1030,6 +1033,13 @@ namespace dlib
const float alpha = 1;
const float beta = add_to_output ? 1 : 0;
// Since cudnnConvolutionForward() is an asynchronous call, we need to hold a
// reference to the workspace buffer so we can be sure it isn't reallocated
// while the function is still executing on the device. But each time we come
// here, we make sure to grab the latest workspace buffer so that, globally, we
// minimize the number of such buffers.
forward_workspace = workspace->get(forward_workspace_size_in_bytes);
CHECK_CUDNN(cudnnConvolutionForward(
context(),
&alpha,
@ -1039,7 +1049,7 @@ namespace dlib
filters.device(),
(const cudnnConvolutionDescriptor_t)conv_handle,
(cudnnConvolutionFwdAlgo_t)forward_algo,
workspace->get(forward_workspace_size_in_bytes),
forward_workspace,
forward_workspace_size_in_bytes,
&beta,
descriptor(output),
@ -1056,6 +1066,13 @@ namespace dlib
const float alpha = 1;
const float beta = add_to_output ? 1 : 0;
// Since cudnnConvolutionBackwardData() is an asynchronous call, we need to hold a
// reference to the workspace buffer so we can be sure it isn't reallocated
// while the function is still executing on the device. But each time we come
// here, we make sure to grab the latest workspace buffer so that, globally, we
// minimize the number of such buffers.
backward_data_workspace = workspace->get(backward_data_workspace_size_in_bytes);
CHECK_CUDNN(cudnnConvolutionBackwardData(context(),
&alpha,
@ -1065,7 +1082,7 @@ namespace dlib
gradient_input.device(),
(const cudnnConvolutionDescriptor_t)conv_handle,
(cudnnConvolutionBwdDataAlgo_t)backward_data_algo,
workspace->get(backward_data_workspace_size_in_bytes),
backward_data_workspace,
backward_data_workspace_size_in_bytes,
&beta,
descriptor(data_gradient),
@ -1082,6 +1099,14 @@ namespace dlib
{
const float alpha = 1;
const float beta = add_to_output ? 1 : 0;
// Since cudnnConvolutionBackwardFilter() is an asynchronous call, we need to hold a
// reference to the workspace buffer so we can be sure it isn't reallocated
// while the function is still executing on the device. But each time we come
// here, we make sure to grab the latest workspace buffer so that, globally, we
// minimize the number of such buffers.
backward_filters_workspace = workspace->get(backward_filters_workspace_size_in_bytes);
CHECK_CUDNN(cudnnConvolutionBackwardFilter(context(),
&alpha,
descriptor(data),
@ -1090,7 +1115,7 @@ namespace dlib
gradient_input.device(),
(const cudnnConvolutionDescriptor_t)conv_handle,
(cudnnConvolutionBwdFilterAlgo_t)backward_filters_algo,
workspace->get(backward_filters_workspace_size_in_bytes),
backward_filters_workspace,
backward_filters_workspace_size_in_bytes,
&beta,
(const cudnnFilterDescriptor_t)filter_handle,

3
dlib/dnn/cudnn_dlibapi.h
View File

@ -269,6 +269,9 @@ namespace dlib
size_t backward_data_workspace_size_in_bytes;
size_t backward_filters_workspace_size_in_bytes;
std::shared_ptr<resizable_cuda_buffer> workspace;
cuda_data_void_ptr forward_workspace;
cuda_data_void_ptr backward_data_workspace;
cuda_data_void_ptr backward_filters_workspace;
};
// ------------------------------------------------------------------------------------