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aebf3b47ae
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9939 Pull Request resolved: https://github.com/facebookresearch/weakly-supervised-action-detection/pull/13 Pull Request resolved: https://github.com/pytorch/translate/pull/166 Pull Request resolved: https://github.com/pytorch/pytorch/pull/9125 Closes https://github.com/pytorch/pytorch/pull/9125 Use inheritance for polymorphism, and remove template parameter This is to change the templating in call sites, the core implementations will change later Before Caffe2 Tensor class was compile-time fixed to bind to a particular device/context. With this change, we're making it a runtime property (stored inside the tensor), but preserve the same semantics. For example, one has to specify device type in order to create a Tensor - there are no uninitialized tensors. More specifically the changes are: 1. We added an extra argument *DeviceType* to most of the constructors of the tensor, e.g. (Tensor(DeviceType type)), 2. Semantics of constructor Tensor(const Tensor<SrcContext>& src, ContextForCopy* context); is changed, in this constructor, the second context is passed in to enable us to call the templated Copy function, it could be in a different context as source and target previously, now we'll enforce that the context should have same device type as src, if it is provided. 3. To preserve 'get-or-construct' semantics of Blob, we added specialized getter Blob::GetMutableTensor that verifies both that Blob contains a Tensor and that it's of a correct type 4. Specifically, Tensor type is not default-constructible any more (as we don't have unknown device tensors) and thus some of the code handling STL containers needs to change Note: Some changes are postponed just to keep this diff a bit smaller. Please see `TODO`s. Reviewed By: ezyang, houseroad Differential Revision: D9024330 fbshipit-source-id: e0b8295d2dc6ebe2963383ded5af799ad17164ba
27 lines
905 B
C++
27 lines
905 B
C++
#include "caffe2/core/context_gpu.h"
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#include "caffe2/operators/conv_op_shared.h"
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namespace caffe2 {
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template <>
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void createSharedBuffer<CUDAContext>(Workspace* ws) {
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auto* mutexPtr = ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_CUDA_MUTEX__")
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->GetMutable<std::unique_ptr<std::mutex>>();
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mutexPtr->reset(new std::mutex());
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ws->CreateBlob("__CAFFE2_SHARED_CONV_BUFFER_CUDA__");
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}
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template <>
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void runWithSharedBuffer<CUDAContext>(
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Workspace* ws,
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std::function<void(Tensor* buffer)> f) {
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auto* mutexBlob = ws->GetBlob("__CAFFE2_SHARED_CONV_BUFFER_CUDA_MUTEX__");
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CAFFE_ENFORCE(mutexBlob, "Must call createSharedBuffer() first");
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auto* mutexPtr = mutexBlob->GetMutable<std::unique_ptr<std::mutex>>();
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std::lock_guard<std::mutex> g(**mutexPtr);
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auto* buffer =
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ws->GetBlob("__CAFFE2_SHARED_CONV_BUFFER_CUDA__")->GetMutableTensor(CUDA);
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f(buffer);
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}
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}
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