enhance/ditu rnn with fc fuse (#12831)
* make fc fuse work with ditu rnn * add ditu rnn data download to CMAKErevert-12864-feature/process_lod_grad
Yan Chunwei
7 years ago
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78415f326d
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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 <sys/time.h>
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#include <algorithm>
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#include <sstream>
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#include <string>
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#include <vector>
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#include "paddle/fluid/inference/api/paddle_inference_api.h"
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namespace paddle {
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namespace inference {
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// Timer for timer
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class Timer {
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public:
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double start;
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double startu;
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void tic() {
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struct timeval tp;
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gettimeofday(&tp, NULL);
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start = tp.tv_sec;
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startu = tp.tv_usec;
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}
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double toc() {
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struct timeval tp;
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gettimeofday(&tp, NULL);
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double used_time_ms =
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(tp.tv_sec - start) * 1000.0 + (tp.tv_usec - startu) / 1000.0;
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return used_time_ms;
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}
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};
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void split(const std::string &str, char sep, std::vector<std::string> *pieces) {
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pieces->clear();
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if (str.empty()) {
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return;
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}
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size_t pos = 0;
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size_t next = str.find(sep, pos);
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while (next != std::string::npos) {
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pieces->push_back(str.substr(pos, next - pos));
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pos = next + 1;
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next = str.find(sep, pos);
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}
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if (!str.substr(pos).empty()) {
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pieces->push_back(str.substr(pos));
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}
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}
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void split_to_float(const std::string &str, char sep, std::vector<float> *fs) {
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std::vector<std::string> pieces;
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split(str, sep, &pieces);
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std::transform(pieces.begin(), pieces.end(), std::back_inserter(*fs),
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[](const std::string &v) { return std::stof(v); });
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}
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template <typename T>
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std::string to_string(const std::vector<T> &vec) {
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std::stringstream ss;
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for (const auto &c : vec) {
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ss << c << " ";
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}
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return ss.str();
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}
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template <>
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std::string to_string<std::vector<float>>(
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const std::vector<std::vector<float>> &vec) {
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std::stringstream ss;
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for (const auto &piece : vec) {
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ss << to_string(piece) << "\n";
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}
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return ss.str();
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}
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template <>
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std::string to_string<std::vector<std::vector<float>>>(
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const std::vector<std::vector<std::vector<float>>> &vec) {
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std::stringstream ss;
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for (const auto &line : vec) {
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for (const auto &rcd : line) {
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ss << to_string(rcd) << ";\t";
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}
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ss << '\n';
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}
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return ss.str();
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}
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// clang-format off
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void TensorAssignData(PaddleTensor *tensor, const std::vector<std::vector<float>> &data) {
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// Assign buffer
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int dim = std::accumulate(tensor->shape.begin(), tensor->shape.end(), 1, [](int a, int b) { return a * b; });
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tensor->data.Resize(sizeof(float) * dim);
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int c = 0;
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for (const auto &f : data) {
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for (float v : f) { static_cast<float *>(tensor->data.data())[c++] = v; }
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}
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}
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} // namespace inference
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} // namespace paddle
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