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1622546050
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/70248 Modified loops in files under fbsource/fbcode/caffe2/ from the format ``` for(TYPE var=x0;var<x_max;x++) ``` to the format ``` for(const auto var: irange(xmax)) ``` This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand. Test Plan: Sandcastle Reviewed By: malfet Differential Revision: D32813863 fbshipit-source-id: 527244b4a2b220fdfe7f17dee3599603f492a2ca
86 lines
2.5 KiB
C++
86 lines
2.5 KiB
C++
#pragma once
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#include "rebatching_queue.h"
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#include "c10/util/irange.h"
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namespace caffe2 {
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using RebatchingQueuePtr = std::unique_ptr<RebatchingQueue>;
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class CreateRebatchingQueueOp : public Operator<CPUContext> {
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public:
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CreateRebatchingQueueOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator(operator_def, ws) {}
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bool RunOnDevice() override {
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*OperatorBase::Output<RebatchingQueuePtr>(0) =
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RebatchingQueuePtr(new RebatchingQueue(
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OperatorBase::GetSingleArgument<int>("capacity", 1),
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OperatorBase::GetSingleArgument<int>("num_blobs", 1)));
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return true;
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}
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};
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class EnqueueRebatchingQueueOp : public Operator<CPUContext> {
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public:
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EnqueueRebatchingQueueOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator(operator_def, ws),
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enqueueBatch_(
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OperatorBase::GetSingleArgument<bool>("enqueue_batch", false)) {}
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bool RunOnDevice() override {
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auto& queue = Inputs()[0]->template Get<RebatchingQueuePtr>();
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CHECK(queue);
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CAFFE_ENFORCE_EQ(InputSize(), queue->numBlobs() + 1);
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std::vector<const Tensor*> inputTensors;
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inputTensors.reserve(InputSize() - 1);
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for (const auto i : c10::irange(1, InputSize())) {
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inputTensors.push_back(&Input(i));
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}
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return enqueueBatch_ ? queue->enqueueMany(context_, inputTensors)
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: queue->enqueueOne(context_, inputTensors);
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}
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private:
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const bool enqueueBatch_;
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};
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class DequeueRebatchingQueueOp : public Operator<CPUContext> {
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public:
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DequeueRebatchingQueueOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator(operator_def, ws),
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numElements_(OperatorBase::GetSingleArgument<int>("num_elements", 1)) {}
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bool RunOnDevice() override {
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auto& queue = Inputs()[0]->template Get<RebatchingQueuePtr>();
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CHECK(queue);
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std::vector<Tensor*> outputTensors;
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outputTensors.reserve(OutputSize());
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for (const auto i : c10::irange(OutputSize())) {
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outputTensors.push_back(Output(i));
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}
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return queue->dequeue(context_, numElements_, outputTensors);
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}
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private:
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int numElements_;
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};
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class CloseRebatchingQueueOp : public Operator<CPUContext> {
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public:
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CloseRebatchingQueueOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator(operator_def, ws) {}
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bool RunOnDevice() override {
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CAFFE_ENFORCE_EQ(InputSize(), 1);
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auto& queue = Inputs()[0]->template Get<RebatchingQueuePtr>();
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CAFFE_ENFORCE(queue);
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queue->close();
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return true;
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}
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};
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} // namespace caffe2
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