提交 622fe6a5 编写于 作者: L lujun

checkpoint pr be moved here, test=develop

上级 bed0ecf3
......@@ -11,11 +11,11 @@ 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 <fstream>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
#include <string>
#include <vector>
#include "paddle/fluid/operators/load_combine_op.h"
namespace paddle {
namespace operators {
......@@ -30,7 +30,7 @@ class LoadCombineOp : public framework::OperatorWithKernel {
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
framework::OpKernelType kt = framework::OpKernelType(
framework::proto::VarType::FP32, platform::CPUPlace());
framework::proto::VarType::FP32, ctx.GetPlace());
return kt;
}
};
......@@ -75,79 +75,6 @@ that were saved using the SaveCombine operator.
}
};
template <typename DeviceContext, typename T>
class LoadCombineOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto filename = ctx.Attr<std::string>("file_path");
auto load_as_fp16 = ctx.Attr<bool>("load_as_fp16");
auto model_from_memory = ctx.Attr<bool>("model_from_memory");
auto &out_var_names = ctx.Outputs("Out");
PADDLE_ENFORCE_GT(
static_cast<int>(out_var_names.size()), 0,
"The number of output variables should be greater than 0.");
if (!model_from_memory) {
std::ifstream fin(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fin),
"Cannot open file %s for load_combine op", filename);
LoadParamsFromBuffer(ctx, place, &fin, load_as_fp16, out_var_names);
} else {
PADDLE_ENFORCE(!filename.empty(), "Cannot load file from memory");
std::stringstream fin(filename, std::ios::in | std::ios::binary);
LoadParamsFromBuffer(ctx, place, &fin, load_as_fp16, out_var_names);
}
}
void LoadParamsFromBuffer(
const framework::ExecutionContext &context, const platform::Place &place,
std::istream *buffer, bool load_as_fp16,
const std::vector<std::string> &out_var_names) const {
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
auto out_vars = context.MultiOutputVar("Out");
for (size_t i = 0; i < out_var_names.size(); i++) {
PADDLE_ENFORCE(out_vars[i] != nullptr,
"Output variable %s cannot be found", out_var_names[i]);
auto *tensor = out_vars[i]->GetMutable<framework::LoDTensor>();
// Error checking
PADDLE_ENFORCE(static_cast<bool>(*buffer), "Cannot read more");
// Get data from fin to tensor
DeserializeFromStream(*buffer, tensor, dev_ctx);
auto in_dtype = tensor->type();
auto out_dtype =
load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor fp16_tensor;
// copy LoD info to the new tensor
fp16_tensor.set_lod(tensor->lod());
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
// reset output tensor
out_vars[i]->Clear();
tensor = out_vars[i]->GetMutable<framework::LoDTensor>();
tensor->set_lod(fp16_tensor.lod());
tensor->ShareDataWith(fp16_tensor);
}
}
buffer->peek();
PADDLE_ENFORCE(buffer->eof(),
"You are not allowed to load partial data via "
"load_combine_op, use load_op instead.");
}
};
} // namespace operators
} // namespace paddle
......
/* 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 "paddle/fluid/operators/load_combine_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
load_combine,
ops::LoadCombineOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::LoadCombineOpKernel<paddle::platform::CUDADeviceContext, double>,
ops::LoadCombineOpKernel<paddle::platform::CUDADeviceContext, int>,
ops::LoadCombineOpKernel<paddle::platform::CUDADeviceContext, int64_t>);
/* 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 <fstream>
#include <string>
#include <vector>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class LoadCombineOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto filename = ctx.Attr<std::string>("file_path");
auto load_as_fp16 = ctx.Attr<bool>("load_as_fp16");
auto model_from_memory = ctx.Attr<bool>("model_from_memory");
auto &out_var_names = ctx.Outputs("Out");
PADDLE_ENFORCE_GT(
static_cast<int>(out_var_names.size()), 0,
"The number of output variables should be greater than 0.");
if (!model_from_memory) {
std::ifstream fin(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fin),
"Cannot open file %s for load_combine op", filename);
LoadParamsFromBuffer(ctx, place, &fin, load_as_fp16, out_var_names);
} else {
PADDLE_ENFORCE(!filename.empty(), "Cannot load file from memory");
std::stringstream fin(filename, std::ios::in | std::ios::binary);
LoadParamsFromBuffer(ctx, place, &fin, load_as_fp16, out_var_names);
}
}
void LoadParamsFromBuffer(
const framework::ExecutionContext &context, const platform::Place &place,
std::istream *buffer, bool load_as_fp16,
const std::vector<std::string> &out_var_names) const {
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
auto out_vars = context.MultiOutputVar("Out");
for (size_t i = 0; i < out_var_names.size(); i++) {
PADDLE_ENFORCE(out_vars[i] != nullptr,
"Output variable %s cannot be found", out_var_names[i]);
auto *tensor = out_vars[i]->GetMutable<framework::LoDTensor>();
// Error checking
PADDLE_ENFORCE(static_cast<bool>(*buffer), "Cannot read more");
// Get data from fin to tensor
DeserializeFromStream(*buffer, tensor, dev_ctx);
auto in_dtype = tensor->type();
auto out_dtype =
load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor fp16_tensor;
// copy LoD info to the new tensor
fp16_tensor.set_lod(tensor->lod());
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
// reset output tensor
out_vars[i]->Clear();
tensor = out_vars[i]->GetMutable<framework::LoDTensor>();
tensor->set_lod(fp16_tensor.lod());
tensor->ShareDataWith(fp16_tensor);
}
}
buffer->peek();
PADDLE_ENFORCE(buffer->eof(),
"You are not allowed to load partial data via "
"load_combine_op, use load_op instead.");
}
};
} // namespace operators
} // namespace paddle
......@@ -11,12 +11,10 @@ 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 <fstream>
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/profiler.h"
#include <string>
#include "paddle/fluid/operators/load_op.h"
namespace paddle {
namespace operators {
......@@ -56,80 +54,6 @@ class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
}
};
template <typename DeviceContext, typename T>
class LoadOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
auto filename = ctx.Attr<std::string>("file_path");
std::ifstream fin(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s for load op",
filename);
auto out_var_name = ctx.Outputs("Out").data();
auto *out_var = ctx.OutputVar("Out");
PADDLE_ENFORCE(out_var != nullptr, "Output variable %s cannot be found ",
out_var_name);
PADDLE_ENFORCE(out_var != nullptr, "Output variable cannot be found ");
if (out_var->IsType<framework::LoDTensor>()) {
LoadLodTensor(fin, place, out_var, ctx);
} else if (out_var->IsType<framework::SelectedRows>()) {
LoadSelectedRows(fin, place, out_var);
} else {
PADDLE_ENFORCE(
false,
"Load only support LoDTensor and SelectedRows, %s has wrong type",
out_var_name);
}
}
void LoadLodTensor(std::istream &fin, const platform::Place &place,
framework::Variable *var,
const framework::ExecutionContext &ctx) const {
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
auto *tensor = var->GetMutable<framework::LoDTensor>();
DeserializeFromStream(fin, tensor, dev_ctx);
auto load_as_fp16 = ctx.Attr<bool>("load_as_fp16");
auto in_dtype = tensor->type();
auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor fp16_tensor;
// copy LoD info to the new tensor
fp16_tensor.set_lod(tensor->lod());
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
// reset output tensor
var->Clear();
tensor = var->GetMutable<framework::LoDTensor>();
tensor->set_lod(fp16_tensor.lod());
tensor->ShareDataWith(fp16_tensor);
}
}
void LoadSelectedRows(std::istream &fin, const platform::Place &place,
framework::Variable *var) const {
auto *selectedRows = var->GetMutable<framework::SelectedRows>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
framework::DeserializeFromStream(fin, selectedRows, dev_ctx);
selectedRows->SyncIndex();
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
......
/* Copyright (c) 2016 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 "paddle/fluid/operators/load_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
load, ops::LoadOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::LoadOpKernel<paddle::platform::CUDADeviceContext, double>,
ops::LoadOpKernel<paddle::platform::CUDADeviceContext, int>,
ops::LoadOpKernel<paddle::platform::CUDADeviceContext, int64_t>);
/* Copyright (c) 2016 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 <fstream>
#include <string>
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class LoadOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
auto filename = ctx.Attr<std::string>("file_path");
std::ifstream fin(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s for load op",
filename);
auto out_var_name = ctx.Outputs("Out").data();
auto *out_var = ctx.OutputVar("Out");
PADDLE_ENFORCE(out_var != nullptr, "Output variable %s cannot be found ",
out_var_name);
PADDLE_ENFORCE(out_var != nullptr, "Output variable cannot be found ");
if (out_var->IsType<framework::LoDTensor>()) {
LoadLodTensor(fin, place, out_var, ctx);
} else if (out_var->IsType<framework::SelectedRows>()) {
LoadSelectedRows(fin, place, out_var);
} else {
PADDLE_ENFORCE(
false,
"Load only support LoDTensor and SelectedRows, %s has wrong type",
out_var_name);
}
}
void LoadLodTensor(std::istream &fin, const platform::Place &place,
framework::Variable *var,
const framework::ExecutionContext &ctx) const {
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
auto *tensor = var->GetMutable<framework::LoDTensor>();
DeserializeFromStream(fin, tensor, dev_ctx);
auto load_as_fp16 = ctx.Attr<bool>("load_as_fp16");
auto in_dtype = tensor->type();
auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor fp16_tensor;
// copy LoD info to the new tensor
fp16_tensor.set_lod(tensor->lod());
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
// reset output tensor
var->Clear();
tensor = var->GetMutable<framework::LoDTensor>();
tensor->set_lod(fp16_tensor.lod());
tensor->ShareDataWith(fp16_tensor);
}
}
void LoadSelectedRows(std::istream &fin, const platform::Place &place,
framework::Variable *var) const {
auto *selectedRows = var->GetMutable<framework::SelectedRows>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
framework::DeserializeFromStream(fin, selectedRows, dev_ctx);
selectedRows->SyncIndex();
}
};
} // namespace operators
} // namespace paddle
......@@ -12,17 +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 <stdint.h>
#include <fstream>
#include <numeric>
#include <sstream>
#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"
#include "paddle/fluid/platform/port.h"
#include <string>
#include "paddle/fluid/operators/save_combine_op.h"
namespace paddle {
namespace operators {
......@@ -66,67 +58,6 @@ to a file on disk.
}
};
template <typename DeviceContext, typename T>
class SaveCombineOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto filename = ctx.Attr<std::string>("file_path");
auto overwrite = ctx.Attr<bool>("overwrite");
auto save_as_fp16 = ctx.Attr<bool>("save_as_fp16");
bool is_present = FileExists(filename);
if (is_present && !overwrite) {
PADDLE_THROW("%s exists!, cannot save_combine to it when overwrite=false",
filename, overwrite);
}
MkDirRecursively(DirName(filename).c_str());
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
auto &inp_var_names = ctx.Inputs("X");
auto &inp_vars = ctx.MultiInputVar("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);
for (size_t i = 0; i < inp_var_names.size(); i++) {
PADDLE_ENFORCE(inp_vars[i] != nullptr,
"Cannot find variable %s for save_combine_op",
inp_var_names[i]);
PADDLE_ENFORCE(inp_vars[i]->IsType<framework::LoDTensor>(),
"SaveCombineOp only supports LoDTensor, %s has wrong type",
inp_var_names[i]);
auto &tensor = inp_vars[i]->Get<framework::LoDTensor>();
// Serialize tensors one by one
// Check types to see if a fp16 transformation is required
auto in_dtype = tensor.type();
auto out_dtype =
save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor out;
// copy LoD info to the new tensor
out.set_lod(tensor.lod());
framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
framework::SerializeToStream(fout, out, dev_ctx);
} else {
framework::SerializeToStream(fout, tensor, dev_ctx);
}
}
fout.close();
}
};
} // namespace operators
} // namespace paddle
......
/* 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 "paddle/fluid/operators/save_combine_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
save_combine,
ops::SaveCombineOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::SaveCombineOpKernel<paddle::platform::CUDADeviceContext, double>,
ops::SaveCombineOpKernel<paddle::platform::CUDADeviceContext, int>,
ops::SaveCombineOpKernel<paddle::platform::CUDADeviceContext, int64_t>);
/* 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 <stdint.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"
#include "paddle/fluid/platform/port.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class SaveCombineOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto filename = ctx.Attr<std::string>("file_path");
auto overwrite = ctx.Attr<bool>("overwrite");
auto save_as_fp16 = ctx.Attr<bool>("save_as_fp16");
bool is_present = FileExists(filename);
if (is_present && !overwrite) {
PADDLE_THROW("%s exists!, cannot save_combine to it when overwrite=false",
filename, overwrite);
}
MkDirRecursively(DirName(filename).c_str());
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
auto &inp_var_names = ctx.Inputs("X");
auto &inp_vars = ctx.MultiInputVar("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);
for (size_t i = 0; i < inp_var_names.size(); i++) {
PADDLE_ENFORCE(inp_vars[i] != nullptr,
"Cannot find variable %s for save_combine_op",
inp_var_names[i]);
PADDLE_ENFORCE(inp_vars[i]->IsType<framework::LoDTensor>(),
"SaveCombineOp only supports LoDTensor, %s has wrong type",
inp_var_names[i]);
auto &tensor = inp_vars[i]->Get<framework::LoDTensor>();
// Serialize tensors one by one
// Check types to see if a fp16 transformation is required
auto in_dtype = tensor.type();
auto out_dtype =
save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor out;
// copy LoD info to the new tensor
out.set_lod(tensor.lod());
framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
framework::SerializeToStream(fout, out, dev_ctx);
} else {
framework::SerializeToStream(fout, tensor, dev_ctx);
}
}
fout.close();
}
};
} // namespace operators
} // namespace paddle
......@@ -15,28 +15,13 @@ limitations under the License. */
#include <stdint.h>
#include <fstream>
#include <numeric>
#include <string>
#include <vector>
#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/framework/selected_rows.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/operators/save_op.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
using LoDTensor = framework::LoDTensor;
// define LOOKUP_TABLE_PATH for checkpoint notify to save lookup table variables
// to directory specified.
constexpr char LOOKUP_TABLE_PATH[] = "kLookupTablePath";
class SaveOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
......@@ -97,102 +82,6 @@ class SaveOpShapeInference : public framework::InferShapeBase {
void operator()(framework::InferShapeContext *ctx) const override {}
};
template <typename DeviceContext, typename T>
class SaveOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto *input_var = ctx.InputVar("X");
auto iname = ctx.Inputs("X").data();
PADDLE_ENFORCE(input_var != nullptr, "Cannot find variable %s for save_op",
iname);
if (input_var->IsType<framework::LoDTensor>()) {
SaveLodTensor(ctx, place, input_var);
} else if (input_var->IsType<framework::SelectedRows>()) {
SaveSelectedRows(ctx, place, input_var);
} else {
PADDLE_ENFORCE(
false,
"SaveOp only support LoDTensor and SelectedRows, %s has wrong type",
iname);
}
}
void SaveLodTensor(const framework::ExecutionContext &ctx,
const platform::Place &place,
const framework::Variable *var) const {
auto filename = ctx.Attr<std::string>("file_path");
auto overwrite = ctx.Attr<bool>("overwrite");
if (FileExists(filename) && !overwrite) {
PADDLE_THROW("%s is existed, cannot save to it when overwrite=false",
filename, overwrite);
}
MkDirRecursively(DirName(filename).c_str());
auto &tensor = var->Get<framework::LoDTensor>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
auto save_as_fp16 = ctx.Attr<bool>("save_as_fp16");
auto in_dtype = tensor.type();
auto out_dtype = save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor out;
framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
// copy LoD info to the new tensor
out.set_lod(tensor.lod());
framework::SerializeToStream(fout, out, dev_ctx);
} else {
framework::SerializeToStream(fout, tensor, dev_ctx);
}
fout.close();
}
void SaveSelectedRows(const framework::ExecutionContext &ctx,
const platform::Place &place,
const framework::Variable *var) const {
framework::Variable *out_put_var = ctx.OutputVar(LOOKUP_TABLE_PATH);
PADDLE_ENFORCE(
out_put_var != nullptr,
"Can not find variable kLookupTablePath for SaveSelectedRows");
auto *lt_var = out_put_var->GetMutable<std::string>();
std::string filename = lt_var->data();
VLOG(4) << "SaveSelectedRows get File name: " << filename;
MkDirRecursively(DirName(filename).c_str());
auto &selectedRows = var->Get<framework::SelectedRows>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
framework::SerializeToStream(fout, selectedRows, dev_ctx);
fout.close();
}
};
} // namespace operators
} // namespace paddle
......
/* Copyright (c) 2016 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 "paddle/fluid/operators/save_op.h"
#include "paddle/fluid/platform/float16.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
save, ops::SaveOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::SaveOpKernel<paddle::platform::CUDADeviceContext, double>,
ops::SaveOpKernel<paddle::platform::CUDADeviceContext, int>,
ops::SaveOpKernel<paddle::platform::CUDADeviceContext, int64_t>,
ops::SaveOpKernel<paddle::platform::CUDADeviceContext,
paddle::platform::float16>);
/* Copyright (c) 2016 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 <stdint.h>
#include <fstream>
#include <numeric>
#include <string>
#include <vector>
#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/framework/selected_rows.h"
#include "paddle/fluid/framework/variable.h"
namespace paddle {
namespace operators {
// define LOOKUP_TABLE_PATH for checkpoint notify to save lookup table variables
// to directory specified.
constexpr char LOOKUP_TABLE_PATH[] = "kLookupTablePath";
template <typename DeviceContext, typename T>
class SaveOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto place = ctx.GetPlace();
auto *input_var = ctx.InputVar("X");
auto iname = ctx.Inputs("X").data();
PADDLE_ENFORCE(input_var != nullptr, "Cannot find variable %s for save_op",
iname);
if (input_var->IsType<framework::LoDTensor>()) {
SaveLodTensor(ctx, place, input_var);
} else if (input_var->IsType<framework::SelectedRows>()) {
SaveSelectedRows(ctx, place, input_var);
} else {
PADDLE_ENFORCE(
false,
"SaveOp only support LoDTensor and SelectedRows, %s has wrong type",
iname);
}
}
void SaveLodTensor(const framework::ExecutionContext &ctx,
const platform::Place &place,
const framework::Variable *var) const {
auto filename = ctx.Attr<std::string>("file_path");
auto overwrite = ctx.Attr<bool>("overwrite");
if (FileExists(filename) && !overwrite) {
PADDLE_THROW("%s is existed, cannot save to it when overwrite=false",
filename, overwrite);
}
MkDirRecursively(DirName(filename).c_str());
auto &tensor = var->Get<framework::LoDTensor>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
auto save_as_fp16 = ctx.Attr<bool>("save_as_fp16");
auto in_dtype = tensor.type();
auto out_dtype = save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
if (in_dtype != out_dtype) {
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor out;
framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
// copy LoD info to the new tensor
out.set_lod(tensor.lod());
framework::SerializeToStream(fout, out, dev_ctx);
} else {
framework::SerializeToStream(fout, tensor, dev_ctx);
}
fout.close();
}
void SaveSelectedRows(const framework::ExecutionContext &ctx,
const platform::Place &place,
const framework::Variable *var) const {
framework::Variable *out_put_var = ctx.OutputVar(LOOKUP_TABLE_PATH);
PADDLE_ENFORCE(
out_put_var != nullptr,
"Can not find variable kLookupTablePath for SaveSelectedRows");
auto *lt_var = out_put_var->GetMutable<std::string>();
std::string filename = lt_var->data();
VLOG(4) << "SaveSelectedRows get File name: " << filename;
MkDirRecursively(DirName(filename).c_str());
auto &selectedRows = var->Get<framework::SelectedRows>();
// get device context from pool
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &dev_ctx = *pool.Get(place);
// FIXME(yuyang18): We save variable to local file now, but we should change
// it to save an output stream.
std::ofstream fout(filename, std::ios::binary);
PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
filename);
framework::SerializeToStream(fout, selectedRows, dev_ctx);
fout.close();
}
};
} // namespace operators
} // namespace paddle
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