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提交 be050565 编写于 作者: T tangwei12
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delete old checkpoint code

上级 ed2129cc
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Showing with 32 addition and 508 deletion
paddle/fluid/operators/CMakeLists.txt
浏览文件 @ be050565
......@@ -252,8 +252,6 @@ op_library(save_op DEPS lod_tensor)
op_library(load_op DEPS lod_tensor)
op_library(save_combine_op DEPS lod_tensor)
op_library(load_combine_op DEPS lod_tensor)
op_library(checkpoint_save_op DEPS lod_tensor)
op_library(checkpoint_load_op DEPS lod_tensor)
op_library(concat_op DEPS concat)
# FIXME(thuan): Move CSP operators to paddle/fluid/framework/operators/concurrency
......@@ -294,6 +292,5 @@ cc_test(beam_search_op_test SRCS beam_search_op_test.cc DEPS lod_tensor beam_sea
cc_test(strided_memcpy_test SRCS strided_memcpy_test.cc DEPS tensor memory)
cc_test(save_load_op_test SRCS save_load_op_test.cc DEPS save_op load_op)
cc_test(save_load_combine_op_test SRCS save_load_combine_op_test.cc DEPS save_combine_op load_combine_op)
cc_test(checkpoint_op_test SRCS checkpoint_op_test.cc DEPS checkpoint_save_op checkpoint_load_op)
nv_test(nccl_op_test SRCS nccl_op_test.cu.cc DEPS nccl_op gpu_info device_context)
nv_test(dropout_op_test SRCS dropout_op_test.cc DEPS dropout_op tensor)
paddle/fluid/operators/checkpoint_load_op.cc 已删除 100644 → 0
浏览文件 @ ed2129cc
/* 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 <stdint.h>
#include <sys/stat.h>
#include <fstream>
#include <numeric>
#include <sstream>
#include <streambuf>
#include <string>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
namespace paddle {
namespace operators {
constexpr char kSEP = '/';
// write empty file named _SUCCESS
const char SUCCESS[] = "_SUCCESS";
const char SERIAL_VAR[] = "SERIAL_NUMBER";
static bool FileExists(const std::string &filepath) {
struct stat buffer;
return (stat(filepath.c_str(), &buffer) == 0);
}
static std::string GenePath(const std::string &dir, const std::string &file) {
std::string file_path;
file_path.append(file_path);
file_path.append("/");
file_path.append(file);
return file_path;
}
static bool IsNumber(const std::string &s) {
std::string::const_iterator it = s.begin();
while (it != s.end() && std::isdigit(*it)) ++it;
return !s.empty() && it == s.end();
}
static void LoadInputVars(const framework::Scope &scope,
const platform::Place &place,
const std::vector<std::string> &inp_var_names,
const std::string &dir) {
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// todo (tangwei) made it async
for (size_t i = 0; i < inp_var_names.size(); i++) {
auto *var = scope.FindVar(inp_var_names[i]);
PADDLE_ENFORCE(var != nullptr,
"Cannot find variable %s for save_combine_op",
inp_var_names[i]);
PADDLE_ENFORCE(var->IsType<framework::LoDTensor>(),
"LoadCombineOp only supports LoDTensor, %s has wrong type",
inp_var_names[i]);
std::string var_file = GenePath(dir, inp_var_names[i]);
auto *tensor = var->GetMutable<framework::LoDTensor>();
std::ifstream fin(var_file);
PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s for load op",
var_file);
framework::DeserializeFromStream(fin, tensor, dev_ctx);
fin.close();
VLOG(3) << " load var: " << inp_var_names[i] << " finished";
}
}
static void LoadStringArgv(const framework::Scope &scope,
const platform::Place &place,
const std::vector<std::string> &argv,
const std::string &dir) {
for (size_t i = 0; i < argv.size(); i++) {
auto *var = scope.FindVar(argv[i]);
std::string *var_str = var->GetMutable<std::string>();
std::string var_file = GenePath(dir, argv[i]);
std::ifstream fin(var_file);
PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s for load op",
var_file);
std::getline(fin, *var_str);
fin.close();
VLOG(3) << " load String argv: " << argv[i] << " value is: " << var_str;
}
}
class CheckpointLoadOp : public framework::OperatorBase {
public:
CheckpointLoadOp(const std::string &type,
const framework::VariableNameMap &inputs,
const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs)
: OperatorBase(type, inputs, outputs, attrs) {}
private:
void RunImpl(const framework::Scope &scope,
const platform::Place &place) const override {
std::string dir = Attr<std::string>("dir");
std::string serial_num_attr = Attr<std::string>("Serial");
VLOG(3) << "CheckpointLoadOp get Attr dir: " << dir;
VLOG(3) << "CheckpointLoadOp get Attr Serial: " << serial_num_attr;
std::string serial_var_name = std::string(SERIAL_VAR);
auto *serial_var = scope.FindVar(serial_var_name);
PADDLE_ENFORCE(serial_var != nullptr,
"Cannot find variable %s for checkpoint_load_op",
serial_var_name);
auto *serial_num = serial_var->GetMutable<std::string>();
serial_num->clear();
serial_num->append(serial_num_attr);
VLOG(1) << "CheckpointLoadOp set " << SERIAL_VAR
<< " value: " << serial_num;
std::string success = GenePath(dir, serial_num->c_str());
VLOG(3) << "Load checkpoint from dir: " << success;
success = GenePath(success, SUCCESS);
bool is_present = FileExists(success);
if (!is_present) {
VLOG(1) << "CheckpointLoadOp can not find " << SUCCESS
<< " from: " << success;
return;
}
VLOG(3) << "Ready to load vars to scope";
auto inp_var_names = Inputs("X");
PADDLE_ENFORCE_GT(static_cast<int>(inp_var_names.size()), 0,
"The number of input variables should be greater than 0");
LoadInputVars(scope, place, inp_var_names, dir);
// VLOG(3) << "Ready to load string argv to scope";
// auto argv = Output("Argv");
// LoadStringArgv(scope, place, argv, dir);
}
};
class CheckpointLoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput(
"X",
"(vector) Input LoDTensors that need to be saved together in a file.")
.AsDuplicable();
AddOutput(
"Argv",
"(vector) Input LoDTensors that need to be saved together in a file.");
AddComment(R"DOC(
CheckpointLoad operator
This operator will serialize and write a list of input LoDTensor variables
to a file on disk.
)DOC");
AddAttr<std::string>(
"Serial",
"(std::string)"
"The serial number of the checkpoint will to be load.");
AddAttr<std::string>(
"dir",
"(string)"
"The \"dir\" where the checkpoint files will be loaded.")
.AddCustomChecker(
[](const std::string &path) { return !path.empty(); });
}
};
class CheckpointLoadOpVarTypeInference : public framework::VarTypeInference {
public:
void operator()(const framework::OpDesc &op_desc,
framework::BlockDesc *block) const override {
auto out_var_name = op_desc.Output("Argv").front();
auto &out_var = block->FindRecursiveOrCreateVar(out_var_name);
auto var_type = framework::proto::VarType::RAW;
out_var.SetType(var_type);
}
};
class CheckpointLoadOpShapeInference : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext *ctx) const override {}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(checkpoint_load, ops::CheckpointLoadOp,
paddle::framework::EmptyGradOpMaker,
ops::CheckpointLoadOpProtoMaker,
ops::CheckpointLoadOpVarTypeInference,
ops::CheckpointLoadOpShapeInference);
// REGISTER_OPERATOR(checkpoint_load, ops::CheckpointLoadOp,
// ops::CheckpointLoadOpProtoMaker);
paddle/fluid/operators/checkpoint_op_test.cc 已删除 100644 → 0
浏览文件 @ ed2129cc
/* 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 "gtest/gtest.h"
#include "paddle/fluid/framework/op_registry.h"
USE_NO_KERNEL_OP(checkpoint_save)
USE_NO_KERNEL_OP(checkpoint_load)
TEST(CheckpointSaveOp, CPU) {
paddle::framework::Scope scope;
paddle::platform::CPUPlace place;
auto var = scope.Var("test_var");
auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
tensor->Resize({3, 10});
paddle::framework::LoD expect_lod;
expect_lod.resize(1);
expect_lod[0].push_back(0);
expect_lod[0].push_back(1);
expect_lod[0].push_back(2);
expect_lod[0].push_back(3);
tensor->set_lod(expect_lod);
float* expect = tensor->mutable_data<float>(place);
for (int64_t i = 0; i < tensor->numel(); ++i) {
expect[i] = static_cast<float>(paddle::platform::float16(i));
}
scope.Var("SERIAL_NUMBER");
paddle::framework::AttributeMap attrs;
attrs.insert({"dir", std::string("ckpt")});
auto save_op = paddle::framework::OpRegistry::CreateOp(
"checkpoint_save", {{"X", {"test_var"}}}, {}, attrs);
save_op->Run(scope, place);
}
TEST(CheckpointLoadOp, CPU) {
paddle::framework::Scope scope;
paddle::platform::CPUPlace place;
auto var = scope.Var("test_var");
auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
tensor->Resize({3, 10});
paddle::framework::LoD expect_lod;
expect_lod.resize(1);
expect_lod[0].push_back(0);
expect_lod[0].push_back(1);
expect_lod[0].push_back(2);
expect_lod[0].push_back(3);
tensor->set_lod(expect_lod);
float* expect = tensor->mutable_data<float>(place);
for (int64_t i = 0; i < tensor->numel(); ++i) {
expect[i] = static_cast<float>(paddle::platform::float16(i));
}
scope.Var("SERIAL_NUMBER");
auto* serial_num = scope.FindVar("SERIAL_NUMBER")->GetMutable<std::string>();
serial_num->append("0");
paddle::framework::AttributeMap attrs;
attrs.insert({"dir", std::string("ckpt")});
attrs.insert({"Serial", std::string("SERIAL_NUMBER")});
auto load_op = paddle::framework::OpRegistry::CreateOp(
"checkpoint_load", {{"X", {"test_var"}}}, {{"Argv", {}}}, attrs);
load_op->Run(scope, place);
}
paddle/fluid/operators/checkpoint_save_op.cc 已删除 100644 → 0
浏览文件 @ ed2129cc
/* 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 <stdint.h>
#include <sys/stat.h>
#include <fstream>
#include <numeric>
#include <sstream>
#include <string>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
namespace paddle {
namespace operators {
constexpr char kSEP = '/';
// write empty file named _SUCCESS
const char SUCCESS[] = "_SUCCESS";
const char SERIAL_VAR[] = "SERIAL_NUMBER";
static bool IsNumber(const std::string &s) {
std::string::const_iterator it = s.begin();
while (it != s.end() && std::isdigit(*it)) ++it;
return !s.empty() && it == s.end();
}
static std::string GenePath(const std::string &dir, const std::string &file) {
std::string file_path;
file_path.append(dir);
file_path.append("/");
file_path.append(file);
return file_path;
}
static bool FileExists(const std::string &filepath) {
struct stat buffer;
return (stat(filepath.c_str(), &buffer) == 0);
}
static std::string DirName(const std::string &filepath) {
auto pos = filepath.rfind(kSEP);
if (pos == std::string::npos) {
return "";
}
return filepath.substr(0, pos);
}
static void MkDir(const char *path) {
if (mkdir(path, 0755)) {
PADDLE_ENFORCE_EQ(errno, EEXIST, "%s mkdir failed!", path);
}
}
static void MkDirRecursively(const char *fullpath) {
if (*fullpath == '\0') return; // empty string
if (FileExists(fullpath)) return;
MkDirRecursively(DirName(fullpath).c_str());
MkDir(fullpath);
}
class CheckpointSaveOp : public framework::OperatorBase {
public:
CheckpointSaveOp(const std::string &type,
const framework::VariableNameMap &inputs,
const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs)
: OperatorBase(type, inputs, outputs, attrs) {}
private:
void RunImpl(const framework::Scope &scope,
const platform::Place &place) const override {
auto ck_dir = Attr<std::string>("dir");
auto overwrite = Attr<bool>("overwrite");
std::string serial_var_name = std::string(SERIAL_VAR);
auto *serial_num =
scope.FindVar(serial_var_name)->GetMutable<std::string>();
VLOG(1) << "CheckpointSaveOp get " << SERIAL_VAR
<< " value: " << serial_num;
int serials = 0;
if (!serial_num->empty()) {
serials = std::stoi(serial_num->data());
serials += 1;
}
serial_num->clear();
serial_num->append(std::to_string(serials));
std::string dir = GenePath(ck_dir, serial_num->c_str());
VLOG(1) << "CheckpointSaveOp current dir: " << dir;
bool is_present = FileExists(dir);
if (is_present && !overwrite) {
PADDLE_THROW("%s exists!, checkpoint save cannot to overwrite it", dir,
overwrite);
}
MkDirRecursively(dir.c_str());
auto inp_var_names = Inputs("X");
PADDLE_ENFORCE_GT(static_cast<int>(inp_var_names.size()), 0,
"The number of input variables should be greater than 0");
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// todo (tangwei) made it async
for (size_t i = 0; i < inp_var_names.size(); i++) {
auto *var = scope.FindVar(inp_var_names[i]);
PADDLE_ENFORCE(var != nullptr,
"Cannot find variable %s for checkpoint save op",
inp_var_names[i]);
PADDLE_ENFORCE(
var->IsType<framework::LoDTensor>(),
"CheckpointSaveOp only supports LoDTensor, %s has wrong type",
inp_var_names[i]);
auto &tensor = var->Get<framework::LoDTensor>();
// Serialize tensors one by one
std::string var_file = GenePath(dir, inp_var_names[i]);
std::ofstream fout(var_file);
framework::SerializeToStream(fout, tensor, dev_ctx);
fout.close();
}
std::string success = GenePath(dir, SUCCESS);
std::ofstream fout(success);
fout.close();
}
};
class CheckpointSaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput(
"X",
"(vector) Input LoDTensors that need to be saved together in a file.")
.AsDuplicable();
AddComment(R"DOC(
CheckpointSave operator
This operator will serialize and write a list of input LoDTensor variables
to a file on disk.
)DOC");
AddAttr<bool>("overwrite",
"(boolean, default false)"
"Delete the output dir if it exists.")
.SetDefault(false);
AddAttr<std::string>("dir",
"(string)"
"The dir where the LoDTensor variables will be saved.")
.AddCustomChecker(
[](const std::string &path) { return !path.empty(); });
}
};
// class CheckpointSaveOpVarTypeInference : public framework::VarTypeInference {
// public:
// void operator()(const framework::OpDesc &op_desc,
// framework::BlockDesc *block) const override {
// auto out_var_name = op_desc.Output("Serial").front();
// auto &out_var = block->FindRecursiveOrCreateVar(out_var_name);
// auto var_type = framework::proto::VarType::RAW;
// out_var.SetType(var_type);
// }
// };
// class CheckpointSaveOpShapeInference : public framework::InferShapeBase {
// public:
// void operator()(framework::InferShapeContext *ctx) const override {}
// };
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(checkpoint_save, ops::CheckpointSaveOp,
ops::CheckpointSaveOpProtoMaker);
// REGISTER_OPERATOR(checkpoint_save, ops::CheckpointSaveOp,
// paddle::framework::EmptyGradOpMaker,
// ops::CheckpointSaveOpProtoMaker,
// ops::CheckpointSaveOpVarTypeInference,
// ops::CheckpointSaveOpShapeInference);
python/paddle/fluid/framework.py
浏览文件 @ be050565
......@@ -489,8 +489,7 @@ class Operator(object):
'rnn_memory_helper_grad', 'conditional_block', 'while', 'send',
'recv', 'listen_and_serv', 'parallel_do', 'save_combine',
'load_combine', 'ncclInit', 'channel_create', 'channel_close',
'channel_send', 'channel_recv', 'select', 'gen_nccl_id',
'checkpoint_save', 'checkpoint_load'
'channel_send', 'channel_recv', 'select', 'gen_nccl_id'
}
if type not in no_kernel_op_set:
self.desc.infer_var_type(self.block.desc)
......
python/paddle/fluid/io.py
浏览文件 @ be050565
......@@ -455,7 +455,7 @@ def get_parameter_value_by_name(name, executor, program=None):
SUCCESS = "_SUCCESS"
BEGIN_SECS = time.time()
BEGIN_SECS = None
def save_checkpoint(executor,
......@@ -478,13 +478,21 @@ def save_checkpoint(executor,
os.makedirs(dirname)
global BEGIN_SECS
if time.time() - BEGIN_SECS < save_secs:
return
if BEGIN_SECS is not None:
if time.time() - BEGIN_SECS < save_secs:
return
BEGIN_SECS = time.time()
serial = _get_lastest_checkpoint_dir(dirname) + 1
cur_dir = os.path.join(dirname, str(serial))
save_persistables(executor, cur_dir, main_program)
# save_persistables(executor, cur_dir, main_program)
save_vars(
executor,
dirname=cur_dir,
main_program=main_program,
vars=None,
predicate=is_checkpoint_var,
filename=None)
_write_success(cur_dir)
_lru_delete(dirname, keep_max)
......@@ -505,7 +513,25 @@ def restore_checkpoint(dirname, executor, main_program=None):
if serial < 0:
return
cur_dir = os.path.join(dirname, str(serial))
load_persistables(executor, cur_dir, main_program)
# load_persistables(executor, cur_dir, main_program)
load_vars(
executor,
dirname=cur_dir,
main_program=main_program,
predicate=is_checkpoint_var,
filename=None)
def is_checkpoint_var(var):
if var.desc.type() == core.VarDesc.VarType.FEED_MINIBATCH or \
var.desc.type() == core.VarDesc.VarType.FETCH_LIST or \
var.desc.type() == core.VarDesc.VarType.RAW:
return False
if var.name.endswith("@GRAD"):
return False
return var.persistable
def _lru_delete(dirname, keep_max=3):
......
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