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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
43 lines
1.2 KiB
C++
43 lines
1.2 KiB
C++
#include "caffe2/core/context.h"
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#include "caffe2/core/operator.h"
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namespace caffe2 {
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namespace {
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class GetAllBlobNamesOp final : public Operator<CPUContext> {
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public:
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GetAllBlobNamesOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator<CPUContext>(operator_def, ws),
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include_shared_(GetSingleArgument<int>("include_shared", true)),
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ws_(ws) {}
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bool RunOnDevice() override {
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auto* out = Output(0);
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const auto& blobs = include_shared_ ? ws_->Blobs() : ws_->LocalBlobs();
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out->Resize(blobs.size());
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std::copy(
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blobs.begin(), blobs.end(), out->template mutable_data<std::string>());
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return true;
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}
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private:
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bool include_shared_;
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Workspace* ws_;
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};
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REGISTER_CPU_OPERATOR(GetAllBlobNames, GetAllBlobNamesOp);
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OPERATOR_SCHEMA(GetAllBlobNames)
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.NumInputs(0)
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.NumOutputs(1)
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.SetDoc(R"DOC(
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Return a 1D tensor of strings containing the names
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of each blob in the active workspace.
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)DOC")
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.Arg(
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"include_shared",
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"(bool, default true) Whether to include blobs "
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"inherited from parent workspaces.")
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.Output(0, "blob_names", "1D tensor of strings containing blob names.");
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SHOULD_NOT_DO_GRADIENT(GetAllBlobNamesOp);
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}
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}
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