pytorch/caffe2/operators/conv_op_shared.cc

36 lines
1.1 KiB
C++

#include "conv_op_shared.h"
#include "caffe2/core/context.h"
#include "caffe2/core/flags.h"
#include "caffe2/core/workspace.h"
C10_DEFINE_bool(
caffe2_force_shared_col_buffer,
false,
"Always use the shared col buffer");
namespace caffe2 {
template <>
void createSharedBuffer<CPUContext>(Workspace* ws) {
auto* mutexPtr = ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_CPU_MUTEX__")
->GetMutable<std::unique_ptr<std::mutex>>();
// NOLINTNEXTLINE(modernize-make-unique)
mutexPtr->reset(new std::mutex());
ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_CPU__");
}
template <>
void runWithSharedBuffer<CPUContext>(
Workspace* ws,
std::function<void(Tensor* buffer)> f) {
auto* mutexBlob = ws->GetBlob("__CAFFE2_SHARED_CONV_BUFFER_CPU_MUTEX__");
CAFFE_ENFORCE(mutexBlob, "Must call createSharedBuffer() first");
auto* mutexPtr = mutexBlob->GetMutable<std::unique_ptr<std::mutex>>();
std::lock_guard<std::mutex> g(**mutexPtr);
auto* buffer = BlobGetMutableTensor(
ws->GetBlob("__CAFFE2_SHARED_CONV_BUFFER_CPU__"), CPU);
f(buffer);
}
}