mirror of
https://github.com/saymrwulf/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
99 lines
3 KiB
C++
99 lines
3 KiB
C++
/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include "rebatching_queue.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 TensorCPU*> inputTensors;
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inputTensors.reserve(InputSize() - 1);
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for (int i = 1; i < InputSize(); ++i) {
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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<TensorCPU*> outputTensors;
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outputTensors.reserve(OutputSize());
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for (int i = 0; i < OutputSize(); ++i) {
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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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} // caffe2
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