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提交 6bb62d81 编写于 作者: W wangliu
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add timer for debug

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src/io/io.cpp 已删除 100644 → 0
浏览文件 @ f131c79e
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "io/io.h"
#include <fstream>
#include <vector>
#include "common/enforce.h"
#include "common/log.h"
#include "framework/framework.pb-c.h"
#include "framework/lod_tensor.h"
#include "framework/operator.h"
#include "framework/program/program_desc.h"
#include "framework/program/var_desc.h"
#include "framework/scope.h"
#include "framework/tensor.h"
namespace paddle_mobile {
using framework::Variable;
void ReadBinaryFile(const std::string &filename, std::string *contents) {
std::ifstream fin(filename, std::ios::in | std::ios::binary);
PADDLE_MOBILE_ENFORCE(fin.is_open(), "open file: %s failed",
filename.c_str());
fin.seekg(0, std::ios::end);
contents->clear();
contents->resize(fin.tellg());
fin.seekg(0, std::ios::beg);
fin.read(&(contents->at(0)), contents->size());
fin.close();
}
static size_t ReadBuffer(const char *file_name, uint8_t **out) {
printf("%s \n", file_name);
FILE *fp;
fp = fopen(file_name, "rb");
PADDLE_MOBILE_ENFORCE(fp != NULL, " %s open failed !", file_name);
fseek(fp, 0, SEEK_END);
size_t size = ftell(fp);
rewind(fp);
DLOG << "model size: " << size;
*out = reinterpret_cast<uint8_t *>(size);
size_t cur_len = 0;
size_t nread;
while ((nread = fread(*out + cur_len, 1, size - cur_len, fp)) != 0) {
cur_len += nread;
}
fclose(fp);
return cur_len;
}
template <typename Dtype, Precision P>
void Loader<Dtype, P>::LoadVar(framework::Variable *variable,
const framework::VarDesc &var_desc,
const std::string &file_path) {
auto tensor = variable->GetMutable<framework::LoDTensor>();
std::ifstream is(file_path);
PADDLE_MOBILE_ENFORCE(is.is_open(), "open file: %s failed",
file_path.c_str());
std::fpos<mbstate_t> pos;
pos = is.tellg(); // save current position
is.seekg(0, std::ios::end);
is.seekg(pos); // restore saved position
// 1. version
uint32_t version;
is.read(reinterpret_cast<char *>(&version), sizeof(version));
// 2 Lod information
uint64_t lod_level;
is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level));
auto &lod = *tensor->mutable_lod();
lod.resize(lod_level);
for (uint64_t i = 0; i < lod_level; ++i) {
uint64_t size;
is.read(reinterpret_cast<char *>(&size), sizeof(size));
std::vector<size_t> tmp(size / sizeof(size_t));
is.read(reinterpret_cast<char *>(tmp.data()),
static_cast<std::streamsize>(size));
for (auto j : tmp) {
LOG(kLOG_DEBUG1) << " lod - " << j;
}
lod[i] = tmp;
}
// 3. tensor version
uint32_t tensor_version;
is.read(reinterpret_cast<char *>(&tensor_version), sizeof(tensor_version));
// 4. tensor desc
int32_t size;
is.read(reinterpret_cast<char *>(&size), sizeof(size));
std::unique_ptr<char[]> buf(new char[size]);
is.read(reinterpret_cast<char *>(buf.get()), size);
const framework::TensorDesc &desc = var_desc.Tensor_desc();
PaddleMobile__Framework__Proto__VarType__TensorDesc *tensor_desc = NULL;
// void *v;
// PaddleMobile__Framework__Proto__VarType__TensorDesc_Closure()(tensor_desc,
// buf.get());
// DLOG << "PaddleMobile__Framework__Proto__VarType__TensorDesc_Closure- " <<
// tensor_desc;
// framework::TensorDesc &tensor_desc = variable->
// PaddleMobile__Framework__Proto__ProgramDesc *c_program;
// uint8_t *proto_buf = NULL;
// size_t read_size = ReadBuffer(file_path.c_str(), &proto_buf);
// c_program = paddle_mobile__framework__proto__program_desc__unpack(NULL,
// read_size, buf);
// paddle_mobile__framework__proto__var_type__tensor_desc__init()
int memory_size = 1;
for (auto l : desc.Dims()) {
memory_size *= l;
}
tensor->Resize(framework::make_ddim(desc.Dims()));
void *memory = tensor;
int type_size = 0;
switch (desc.DataType()) {
case framework::VARTYPE_TYPE_FP16:
type_size = 2;
break;
case framework::VARTYPE_TYPE_FP32:
type_size = 4;
memory = tensor->mutable_data<float>();
break;
case framework::VARTYPE_TYPE_FP64:
type_size = 8;
break;
case framework::VARTYPE_TYPE_INT32:
type_size = 4;
break;
case framework::VARTYPE_TYPE_INT64:
type_size = 8;
break;
case framework::VARTYPE_TYPE_BOOL:
type_size = 1;
break;
default:
break;
}
is.read(static_cast<char *>(memory), memory_size * type_size);
is.close();
}
template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
const std::string &dirname) {
std::string model_filename = dirname + "/__model__";
PaddleMobile__Framework__Proto__ProgramDesc *c_program;
uint8_t *buf = NULL;
size_t read_size = ReadBuffer(model_filename.c_str(), &buf);
PADDLE_MOBILE_ENFORCE(buf != NULL, "read from __model__ is null");
c_program = paddle_mobile__framework__proto__program_desc__unpack(
NULL, read_size, buf);
PADDLE_MOBILE_ENFORCE(c_program != NULL, "program is null");
DLOG << "n_ops: " << (*c_program->blocks)->n_ops;
std::shared_ptr<framework::ProgramDesc> originProgramDesc =
std::make_shared<framework::ProgramDesc>(c_program);
framework::Program<Dtype, P> program;
program.model_path = dirname;
program.originProgram = originProgramDesc;
std::shared_ptr<framework::Scope> scope =
std::make_shared<framework::Scope>();
program.scope = scope;
originProgramDesc->Block(0);
for (const auto &block : originProgramDesc->Blocks()) {
for (int i = 0; i < block->Vars().size(); ++i) {
std::shared_ptr<framework::VarDesc> var_desc = block->Vars()[i];
// DLOG << "var name-- " << var_desc->Name();
auto var = scope->Var(var_desc->Name());
if (var_desc->Type() == framework::VARTYPE_TYPE_LOD_TENSOR) {
if (var_desc->Persistable() &&
var_desc->Type() != framework::VARTYPE_TYPE_FEED_MINIBATCH &&
var_desc->Type() != framework::VARTYPE_TYPE_FETCH_LIST) {
// DLOG << "to load var ";
auto dim = var_desc->Tensor_desc().Dims();
auto tensor = var->GetMutable<framework::LoDTensor>();
tensor->Resize(framework::make_ddim(dim));
} else {
auto dim = var_desc->Tensor_desc().Dims();
PADDLE_MOBILE_ENFORCE(dim.size() > 0, "dim size is 0");
dim[0] = 1;
auto tensor = var->GetMutable<framework::LoDTensor>();
tensor->Resize(framework::make_ddim(dim));
}
} else {
// TODO(codeWorm): some.
}
}
}
originProgramDesc->Description("program: ");
paddle_mobile__framework__proto__program_desc__free_unpacked(c_program, NULL);
return program;
}
template class Loader<CPU, Precision::FP32>;
#pragma mark - executor
template <typename Dtype, Precision P>
Executor<Dtype, P>::Executor(const framework::Program<Dtype> p) : program_(p) {
if (use_optimize_) {
to_predict_program_ = program_.optimizeProgram;
} else {
to_predict_program_ = program_.originProgram;
}
const std::vector<std::shared_ptr<framework::BlockDesc>> blocks =
to_predict_program_->Blocks();
for (int i = 0; i < blocks.size(); ++i) {
std::shared_ptr<framework::BlockDesc> block_desc = blocks[i];
std::vector<std::shared_ptr<framework::OpDesc>> ops = block_desc->Ops();
for (int j = 0; j < ops.size(); ++j) {
std::shared_ptr<framework::OpDesc> op = ops[j];
auto op_base = framework::OpRegistry<Dtype>::CreateOp(
op->Type(), op->GetInputs(), op->GetOutputs(), op->GetAttrMap(),
program_.scope);
op_base->InferShape();
ops_of_block_[*block_desc.get()].push_back(op_base);
}
}
InitMemory();
}
template <typename Dtype, Precision P>
Executor<Dtype, P>::Executor(const framework::Program<Dtype> p, int batch_size)
: program_(p), batch_size_(batch_size) {
if (use_optimize_) {
to_predict_program_ = program_.optimizeProgram;
} else {
to_predict_program_ = program_.originProgram;
}
Variable *variable_ptr = program_.scope->Var("batch_size");
variable_ptr[0].SetValue<int>(batch_size);
const std::vector<std::shared_ptr<framework::BlockDesc>> blocks =
to_predict_program_->Blocks();
for (int i = 0; i < blocks.size(); ++i) {
std::shared_ptr<framework::BlockDesc> block_desc = blocks[i];
std::vector<std::shared_ptr<framework::OpDesc>> ops = block_desc->Ops();
for (int j = 0; j < ops.size(); ++j) {
std::shared_ptr<framework::OpDesc> op = ops[j];
auto op_base = framework::OpRegistry<Dtype>::CreateOp(
op->Type(), op->GetInputs(), op->GetOutputs(), op->GetAttrMap(),
program_.scope);
op_base->InferShape();
ops_of_block_[*block_desc.get()].push_back(op_base);
}
}
InitMemory();
}
template <typename Dtype, Precision P>
void Executor<Dtype, P>::LoadMemory(const framework::VarDesc var_desc,
framework::LoDTensor *tensor,
const std::string &file_path) {
std::ifstream is(file_path);
PADDLE_MOBILE_ENFORCE(is.is_open(), "open file: %s failed",
file_path.c_str());
std::fpos<mbstate_t> pos;
pos = is.tellg(); // save current position
is.seekg(0, std::ios::end);
is.seekg(pos); // restore saved position
// 1. version
uint32_t version;
is.read(reinterpret_cast<char *>(&version), sizeof(version));
// 2 Lod information
uint64_t lod_level;
is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level));
auto &lod = *tensor->mutable_lod();
lod.resize(lod_level);
for (uint64_t i = 0; i < lod_level; ++i) {
uint64_t size;
is.read(reinterpret_cast<char *>(&size), sizeof(size));
std::vector<size_t> tmp(size / sizeof(size_t));
is.read(reinterpret_cast<char *>(tmp.data()),
static_cast<std::streamsize>(size));
for (auto j : tmp) {
LOG(kLOG_DEBUG1) << " lod - " << j;
}
lod[i] = tmp;
}
// 3. tensor version
uint32_t tensor_version;
is.read(reinterpret_cast<char *>(&tensor_version), sizeof(tensor_version));
// 4. tensor desc
int32_t size;
is.read(reinterpret_cast<char *>(&size), sizeof(size));
std::unique_ptr<char[]> buf(new char[size]);
is.read(reinterpret_cast<char *>(buf.get()), size);
const framework::TensorDesc &desc = var_desc.Tensor_desc();
int memory_size = 1;
for (auto l : desc.Dims()) {
memory_size *= l;
}
tensor->Resize(framework::make_ddim(desc.Dims()));
void *memory = tensor;
int type_size = 0;
switch (desc.DataType()) {
case framework::VARTYPE_TYPE_FP16:
type_size = 2;
break;
case framework::VARTYPE_TYPE_FP32:
type_size = 4;
memory = tensor->mutable_data<float>();
break;
case framework::VARTYPE_TYPE_FP64:
type_size = 8;
break;
case framework::VARTYPE_TYPE_INT32:
type_size = 4;
break;
case framework::VARTYPE_TYPE_INT64:
type_size = 8;
break;
case framework::VARTYPE_TYPE_BOOL:
type_size = 1;
break;
default:
break;
}
is.read(static_cast<char *>(memory), memory_size * type_size);
is.close();
}
template <typename Dtype, Precision P>
void Executor<Dtype, P>::InitMemory() {
for (const auto &block : to_predict_program_->Blocks()) {
for (const auto &var_desc : block->Vars()) {
auto var = program_.scope->Var(var_desc->Name());
if (var_desc->Persistable()) {
auto tensor = var->template GetMutable<framework::LoDTensor>();
if (var_desc->Name() == "feed" || var_desc->Name() == "fetch") {
continue;
}
LoadMemory(*var_desc, tensor,
program_.model_path + "/" + var_desc->Name());
} else {
if (var_desc->Type() == framework::VARTYPE_TYPE_LOD_TENSOR) {
auto tensor = var->template GetMutable<framework::LoDTensor>();
tensor->template mutable_data<Ptype>();
}
}
}
}
}
template <typename Dtype, Precision P>
void Executor<Dtype, P>::predict(const framework::Tensor &t, int block_id) {
framework::Variable *g_feed_value = program_.scope->Var("feed");
framework::Tensor *feed_tensor =
g_feed_value->GetMutable<framework::LoDTensor>();
feed_tensor->Resize(t.dims());
feed_tensor->ShareDataWith(t);
std::shared_ptr<framework::BlockDesc> to_predict_block =
to_predict_program_->Block(block_id);
for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size(); ++j) {
auto op = ops_of_block_[*to_predict_block.get()][j];
op->Run();
}
}
template <typename Dtype, Precision P>
std::vector<typename Executor<Dtype, P>::Ptype> Executor<Dtype, P>::predict(
const std::vector<Ptype> &input, const std::vector<int64_t> &dims) {
framework::Tensor tensor(input, framework::make_ddim(dims));
predict(tensor, 0);
framework::Variable *g_feed_value = program_.scope->Var("col");
auto feed_tensor = g_feed_value->GetMutable<framework::Tensor>();
return {};
}
template class Executor<CPU, Precision::FP32>;
} // namespace paddle_mobile
src/io/io.h 已删除 100644 → 0
浏览文件 @ f131c79e
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <memory.h>
#include <string>
#include <vector>
#include "common/types.h"
#include "framework/lod_tensor.h"
#include "framework/operator.h"
#include "framework/paddle_mobile_object.h"
#include "framework/program/program.h"
#include "framework/tensor.h"
namespace paddle_mobile {
template <typename Dtype, Precision P = Precision::FP32>
class Loader : PaddleMobileObject {
public:
const framework::Program<Dtype, P> Load(const std::string &dirname);
private:
void LoadVar(framework::Variable *variable,
const framework::VarDesc &var_desc,
const std::string &file_path);
};
template <typename Dtype, Precision P = Precision::FP32>
class Executor {
public:
typedef typename PrecisionTrait<P>::ptype Ptype;
Executor() = default;
Executor(const framework::Program<Dtype> p);
Executor(const framework::Program<Dtype> p, int batch_size);
std::shared_ptr<framework::Tensor> predict(framework::Tensor &t);
std::vector<Ptype> predict(const std::vector<Ptype> &input,
const std::vector<int64_t> &dims);
protected:
void InitMemory();
void LoadMemory(const framework::VarDesc var_desc,
framework::LoDTensor *tensor, const std::string &file_path);
framework::Program<Dtype> program_;
int batch_size_ = 1;
std::shared_ptr<framework::ProgramDesc> to_predict_program_;
void predict(const framework::Tensor &t, int block_id);
std::map<framework::BlockDesc,
std::vector<std::shared_ptr<framework::OperatorBase<Dtype>>>>
ops_of_block_;
bool use_optimize_ = false;
};
} // namespace paddle_mobile
test/executor_for_test.h
浏览文件 @ 6bb62d81
......@@ -17,9 +17,9 @@ limitations under the License. */
#include <string>
#include <vector>
#include "common/io.h"
#include "common/log.h"
#include "framework/op_registry.h"
#include "io/io.h"
#include "operators/conv_op.h"
#include "operators/elementwise_add_op.h"
#include "operators/pool_op.h"
......
test/framework/test_load.cpp
浏览文件 @ 6bb62d81
......@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/framework/test_optimize.cpp
浏览文件 @ 6bb62d81
......@@ -12,9 +12,9 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "common/io.h"
#include "framework/program/program-optimize/node.h"
#include "framework/program/program-optimize/program_optimize.h"
#include "io/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/net/test_googlenet.cpp
浏览文件 @ 6bb62d81
......@@ -13,25 +13,25 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include <fstream>
#include "../test_helper.h"
#include "../test_include.h"
#include "io/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
// ../../../test/models/googlenet
// ../../../test/models/mobilenet
auto time1 = time();
auto program = loader.Load(std::string("../models/googlenet"));
auto time2 = time();
DLOG << "load cost :" << time_diff(time1, time1) << "ms";
paddle_mobile::Executor<paddle_mobile::CPU> executor(program, 1);
std::vector<float> input;
std::vector<int64_t> dims{1, 3, 224, 224};
GetInput<float>(g_test_image_1x3x224x224, &input, dims);
// DLOG << " input: " << input;
auto time3 = time();
executor.predict(input, dims);
auto time4 = time();
DLOG << "predict cost :" << time_diff(time3, time4) << "ms";
return 0;
}
test/operators/test_pool_op.cpp
浏览文件 @ 6bb62d81
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "../executor_for_test.h"
#include "../test_helper.h"
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/operators/test_reshape_op.cpp
浏览文件 @ 6bb62d81
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "../executor_for_test.h"
#include "../test_helper.h"
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/operators/test_sigmoid_op.cpp
浏览文件 @ 6bb62d81
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "../../src/operators/kernel/sigmoid_kernel.h"
#include "../test_helper.h"
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::framework::Tensor input;
......
test/operators/test_softmax_op.cpp
浏览文件 @ 6bb62d81
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "../executor_for_test.h"
#include "../test_helper.h"
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/operators/test_transpose_op.cpp
浏览文件 @ 6bb62d81
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "../executor_for_test.h"
#include "../test_helper.h"
#include "io/io.h"
#include "common/io.h"
int main() {
paddle_mobile::Loader<paddle_mobile::CPU> loader;
......
test/test_helper.h
浏览文件 @ 6bb62d81
......@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include <chrono>
#include <fstream>
#include <random>
......@@ -31,6 +32,18 @@ static const std::string g_test_image_1x3x224x224 =
"../images/test_image_1x3x224x224_float";
using paddle_mobile::framework::DDim;
using paddle_mobile::framework::Tensor;
using Time = decltype(std::chrono::high_resolution_clock::now());
Time time() { return std::chrono::high_resolution_clock::now(); }
double time_diff(Time t1, Time t2) {
typedef std::chrono::microseconds ms;
auto diff = t2 - t1;
ms counter = std::chrono::duration_cast<ms>(diff);
return counter.count() / 1000.0;
}
template <typename T>
void SetupTensor(paddle_mobile::framework::Tensor *input,
paddle_mobile::framework::DDim dims, T lower, T upper) {
......
test/test_include.h
浏览文件 @ 6bb62d81
......@@ -20,6 +20,7 @@ limitations under the License. */
#include "./test_helper.h"
#include "common/enforce.h"
#include "common/io.h"
#include "common/log.h"
#include "framework/lod_tensor.h"
#include "framework/operator.h"
......@@ -29,4 +30,3 @@ limitations under the License. */
#include "framework/scope.h"
#include "framework/tensor.h"
#include "framework/variable.h"
#include "io/io.h"
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