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https://github.com/saymrwulf/pytorch.git
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553ccccc54
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/47343 Test Plan: Imported from OSS Reviewed By: gmagogsfm Differential Revision: D24723418 Pulled By: wanchaol fbshipit-source-id: 0463819b96c53b12bdbb3905431110d7b21beb77
46 lines
1.3 KiB
C++
46 lines
1.3 KiB
C++
#include <gtest/gtest.h>
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#include "e2e_test_base.h"
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#include <c10d/ProcessGroupGloo.hpp>
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#include <torch/csrc/distributed/rpc/process_group_agent.h>
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#include <torch/csrc/distributed/rpc/request_callback_no_python.h>
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#include <torch/torch.h>
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namespace torch {
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namespace distributed {
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namespace rpc {
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class TestE2EProcessGroup : public TestE2EBase {
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protected:
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void buildRpcAgent() override {
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c10d::ProcessGroupGloo::Options options;
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options.devices.push_back(
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::c10d::ProcessGroupGloo::createDeviceForHostname(serverAddress));
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std::chrono::milliseconds rpcTimeout(30000);
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options.timeout = rpcTimeout;
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// Initialize server rpc agent.
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auto pg = c10::make_intrusive<c10d::ProcessGroupGloo>(
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store, 0, numWorkers, options);
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rpcAgent = std::make_shared<ProcessGroupAgent>(
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"worker",
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pg,
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std::max(16U, std::thread::hardware_concurrency()),
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rpcTimeout,
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std::make_unique<RequestCallbackNoPython>());
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}
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};
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// End to end training loop test in C++ so that we can run LSAN on this test to
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// catch memory leaks. Enabling LSAN with python multiprocessing has been
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// challenging and we don't have a good solution yet.
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TEST_F(TestE2EProcessGroup, TestTrainingLoop) {
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runTrainingLoop();
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}
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} // namespace rpc
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} // namespace distributed
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} // namespace torch
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