Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add-code-exp
ZhenWang
7 years ago
commit
7b9d9d7089
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#include "paddle/fluid/framework/transfer_scope_cache.h"
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namespace paddle {
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namespace framework {
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// Holds all the transfer scope across the process.
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std::unordered_map<size_t, Scope*>& global_transfer_data_cache() {
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typedef std::unordered_map<size_t, Scope*> map_t;
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thread_local std::unique_ptr<map_t> x(new map_t);
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return *x;
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}
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// Holds all the transfer scope for this thread.
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std::unordered_set<Scope*>& global_transfer_scope_cache() {
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typedef std::unordered_set<Scope*> set_t;
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thread_local std::unique_ptr<set_t> x(new set_t);
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return *x;
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}
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// Try to create a transfer scope. If one cached scope has match the
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// requirement, just return that one.
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// Inputs:
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// @type0: the source kernel type.
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// @type1: the target kernel type.
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// @scope: the execution scope of this op.
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// Returns: A scope used to hold the transfer data across the different kernel
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// type.
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Scope* TryCreateTransferScope(OpKernelType type0, OpKernelType type1,
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const Scope* scope) {
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Scope* new_scope{nullptr};
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size_t infer_cache_key =
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CombineHash(OpKernelType::Hash()(type0), OpKernelType::Hash()(type1));
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infer_cache_key =
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CombineHash(infer_cache_key, std::hash<const Scope*>()(scope));
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auto it = global_transfer_data_cache().find(infer_cache_key);
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if (it != global_transfer_data_cache().end()) {
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new_scope = global_transfer_data_cache()[infer_cache_key];
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} else {
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new_scope = &scope->NewScope();
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global_transfer_data_cache()[infer_cache_key] = new_scope;
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}
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global_transfer_scope_cache().insert(new_scope);
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return new_scope;
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}
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} // namespace framework
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} // namespace paddle
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <thread> // NOLINT
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#include <unordered_map>
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#include <unordered_set>
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#include "paddle/fluid/framework/op_kernel_type.h"
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#include "paddle/fluid/framework/scope.h"
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namespace paddle {
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namespace framework {
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std::unordered_map<size_t, Scope*>& global_transfer_data_cache();
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std::unordered_set<Scope*>& global_transfer_scope_cache();
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// Combine two hash values to a single hash.
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static size_t CombineHash(size_t seed, size_t a) {
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return (seed ^ a) + 0x9e3779b9 + (seed << 6) + (seed >> 2);
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}
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Scope* TryCreateTransferScope(OpKernelType type0, OpKernelType type1,
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const Scope* scope);
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void RemoveKidsFromTransferScopeCache(Scope* scope);
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,2 @@
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cc_library(benchmark SRCS benchmark.cc DEPS enforce)
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cc_test(test_benchmark SRCS benchmark_tester.cc DEPS benchmark)
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@ -0,0 +1,49 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#include "paddle/fluid/inference/utils/benchmark.h"
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#include <sstream>
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace inference {
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std::string Benchmark::SerializeToString() const {
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std::stringstream ss;
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ss << "-----------------------------------------------------\n";
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ss << "name\t";
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ss << "batch_size\t";
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ss << "num_threads\t";
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ss << "latency\t";
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ss << "qps";
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ss << '\n';
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ss << name_ << "\t";
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ss << batch_size_ << "\t";
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ss << num_threads_ << "\t";
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ss << latency_ << "\t";
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ss << 1000 / latency_;
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ss << '\n';
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return ss.str();
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}
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void Benchmark::PersistToFile(const std::string &path) const {
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std::ofstream file(path, std::ios::app);
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PADDLE_ENFORCE(file.is_open(), "Can not open %s to add benchmark", path);
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file << SerializeToString();
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file.flush();
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file.close();
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}
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} // namespace inference
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} // namespace paddle
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@ -0,0 +1,52 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#include <fstream>
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#include <iostream>
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namespace paddle {
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namespace inference {
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/*
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* Helper class to calculate the performance.
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*/
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struct Benchmark {
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int batch_size() const { return batch_size_; }
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void SetBatchSize(int x) { batch_size_ = x; }
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int num_threads() const { return num_threads_; }
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void SetNumThreads(int x) { num_threads_ = x; }
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bool use_gpu() const { return use_gpu_; }
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void SetUseGpu() { use_gpu_ = true; }
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int latency() const { return latency_; }
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void SetLatency(int x) { latency_ = x; }
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const std::string& name() const { return name_; }
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void SetName(const std::string& name) { name_ = name; }
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std::string SerializeToString() const;
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void PersistToFile(const std::string& path) const;
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private:
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bool use_gpu_{false};
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int batch_size_{0};
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int latency_;
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int num_threads_{1};
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std::string name_;
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};
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} // namespace inference
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} // namespace paddle
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