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未验证 提交 42e65a20 编写于 作者: Y Yu Yang 提交者： GitHub
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Merge pull request #8791 from reyoung/feature/extract_reader_ops 

Extract create_reader_op to three files
上级 87568cfd 4690b9c9
隐藏空白更改
内联 并排
Showing with 553 addition and 415 deletion
paddle/fluid/framework/reader.cc
浏览文件 @ 42e65a20
......@@ -25,92 +25,5 @@ DDim ReaderBase::shape(size_t idx) const {
return shapes_[idx];
}
void ShuffleReader::ReadNext(std::vector<LoDTensor>* out) {
if (iteration_pos_ >= buffer_.size()) {
// Reload buffer with new data
buffer_.clear();
buffer_.reserve(buffer_size_);
for (int i = 0; i < buffer_size_; ++i) {
if (reader_->HasNext()) {
buffer_.push_back(std::vector<LoDTensor>());
reader_->ReadNext(&buffer_.back());
} else {
break;
}
}
// TODO(fengjiayi): 'std::random_shuffle' can be very slow. It needs to be
// optimize.
std::random_shuffle(buffer_.begin(), buffer_.end());
iteration_pos_ = 0;
}
out->clear();
if (!buffer_.empty()) {
std::swap(*out, buffer_[iteration_pos_++]);
}
// if buffer_ is empty, the 'out' will return as an empty vector.
}
void BatchReader::ReadNext(std::vector<LoDTensor>* out) {
buffer_.clear();
buffer_.reserve(batch_size_);
for (int i = 0; i < batch_size_; ++i) {
if (reader_->HasNext()) {
buffer_.push_back(std::vector<LoDTensor>());
reader_->ReadNext(&buffer_.back());
} else {
break;
}
}
// Concat instances
out->clear();
if (buffer_.empty()) {
// if buffer_ is empty, the 'out' will return as an empty vector.
return;
}
int out_num = buffer_[0].size();
out->reserve(out_num);
for (int j = 0; j < out_num; ++j) {
// Merge shape and check date type
std::type_index batch_type = buffer_[0][j].type();
DDim batch_shape = buffer_[0][j].dims();
for (size_t i = 1; i < buffer_.size(); ++i) {
std::type_index ins_type = buffer_[i][j].type();
DDim ins_shape = buffer_[i][j].dims();
PADDLE_ENFORCE_EQ(batch_type, ins_type);
PADDLE_ENFORCE_EQ(slice_ddim(batch_shape, 1, batch_shape.size()),
slice_ddim(ins_shape, 1, ins_shape.size()));
PADDLE_ENFORCE_GT(ins_shape[0], 0);
batch_shape[0] += ins_shape[0];
}
LoDTensor out_tensor;
out_tensor.Resize(batch_shape);
out_tensor.mutable_data(platform::CPUPlace(), batch_type);
int64_t dst_offset = 0;
// Merge lod and data
LoD batch_lod;
for (size_t i = 0; i < buffer_.size(); ++i) {
DDim ins_shape = buffer_[i][j].dims();
LoD ins_lod = buffer_[i][j].lod();
if (i == 0) {
batch_lod = ins_lod;
} else {
PADDLE_ENFORCE_EQ(batch_lod.size(), ins_lod.size());
for (size_t level_idx = 0; level_idx < batch_lod.size(); ++level_idx) {
auto& lod_level = batch_lod[level_idx];
for (size_t k = 1; k < ins_lod[level_idx].size(); ++k) {
lod_level.push_back(ins_lod[level_idx][k] + lod_level.back());
}
}
}
Tensor dst = out_tensor.Slice(dst_offset, dst_offset + ins_shape[0]);
TensorCopy(buffer_[i][j], platform::CPUPlace(), &dst);
dst_offset += ins_shape[0];
}
out_tensor.set_lod(batch_lod);
out->push_back(out_tensor);
}
}
} // namespace framework
} // namespace paddle
paddle/fluid/framework/reader.h
浏览文件 @ 42e65a20
......@@ -60,83 +60,8 @@ class DecoratedReader : public ReaderBase {
ReaderBase* reader_;
};
// file readers
template <typename T>
class RandomDataGenerator : public FileReader {
public:
RandomDataGenerator(const std::vector<DDim>& shapes, float min, float max)
: FileReader(shapes), min_(min), max_(max) {
PADDLE_ENFORCE_LE(
min, max, "'min' shouldn't be greater than 'max'.(%f vs %f)", min, max);
unsigned int seed = std::random_device()();
engine_.seed(seed);
dist_ = std::uniform_real_distribution<float>(min_, max_);
}
void ReadNext(std::vector<LoDTensor>* out) override {
out->clear();
out->reserve(shapes_.size());
for (const DDim& shape : shapes_) {
PADDLE_ENFORCE_GE(
shape.size(), 2,
"The rank of reader's output data should be 2 at least.(Now it's %d)",
shape.size());
LoDTensor out_tensor;
out_tensor.Resize(shape);
T* data = out_tensor.mutable_data<T>(platform::CPUPlace());
int64_t numel = product(shape);
for (int64_t i = 0; i < numel; ++i) {
data[i] = dist_(engine_);
}
out->push_back(out_tensor);
}
}
bool HasNext() const override { return true; }
void ReInit() override { return; }
private:
float min_;
float max_;
std::minstd_rand engine_;
std::uniform_real_distribution<float> dist_;
};
// decorated readers
class ShuffleReader : public DecoratedReader {
public:
ShuffleReader(ReaderBase* reader, int buffer_size)
: DecoratedReader(reader), buffer_size_(buffer_size), iteration_pos_(0) {
buffer_.reserve(buffer_size);
}
void ReadNext(std::vector<LoDTensor>* out) override;
private:
int buffer_size_;
std::vector<std::vector<LoDTensor>> buffer_;
size_t iteration_pos_;
};
class BatchReader : public DecoratedReader {
public:
BatchReader(ReaderBase* reader, int batch_size)
: DecoratedReader(reader), batch_size_(batch_size) {
buffer_.reserve(batch_size_);
}
void ReadNext(std::vector<LoDTensor>* out) override;
private:
int batch_size_;
std::vector<std::vector<LoDTensor>> buffer_;
};
// The ReaderHolder is used as readers' unified wrapper,
// making it easier to access different type readers in Variables.
// The ReaderHolder is used as reader' unified wrapper,
// making it easier to access different type reader in Variables.
class ReaderHolder {
public:
void Reset(ReaderBase* reader) { reader_.reset(reader); }
......
paddle/fluid/operators/CMakeLists.txt
浏览文件 @ 42e65a20
......@@ -70,7 +70,7 @@ function(op_library TARGET)
endif()
# Define operators that don't need pybind here.
foreach(manual_pybind_op "net_op" "compare_op" "logical_op" "nccl_op" "tensor_array_read_write_op" "create_reader_op")
foreach(manual_pybind_op "net_op" "compare_op" "logical_op" "nccl_op" "tensor_array_read_write_op")
if ("${TARGET}" STREQUAL "${manual_pybind_op}")
set(pybind_flag 1)
endif()
......@@ -128,8 +128,8 @@ else()
set(DEPS_OPS ${DEPS_OPS} nccl_op)
endif()
add_subdirectory(detail)
if(WITH_DISTRIBUTE)
add_subdirectory(detail)
set(DISTRIBUTE_DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
op_library(send_op DEPS ${DISTRIBUTE_DEPS})
......@@ -170,7 +170,6 @@ op_library(recurrent_op DEPS executor)
op_library(warpctc_op DEPS dynload_warpctc sequence_padding sequence_scale)
op_library(cos_sim_op DEPS cos_sim_functor)
op_library(parallel_do_op DEPS executor)
op_library(create_reader_op DEPS reader)
if (WITH_GPU)
op_library(conv_op DEPS vol2col depthwise_conv)
......@@ -189,7 +188,12 @@ list(REMOVE_ITEM GENERAL_OPS ${DEPS_OPS})
foreach(src ${GENERAL_OPS})
op_library(${src})
endforeach()
file(APPEND ${pybind_file} "USE_OP(less_than);\nUSE_OP(logical_and);\nUSE_NO_KERNEL_OP(read_from_array);\nUSE_NO_KERNEL_OP(create_random_data_generator);\n")
file(APPEND ${pybind_file} "USE_OP(less_than);\nUSE_OP(logical_and);\nUSE_NO_KERNEL_OP(read_from_array);\n")
add_subdirectory(reader)
foreach(src ${READER_LIBRARY})
set(OP_LIBRARY ${src} ${OP_LIBRARY})
endforeach()
set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
......
paddle/fluid/operators/create_reader_op.cc 已删除 100644 → 0
浏览文件 @ 87568cfd
// 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/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
namespace paddle {
namespace operators {
static std::vector<framework::DDim> RestoreShapes(
const std::vector<int>& shape_concat, const std::vector<int>& ranks) {
std::vector<framework::DDim> res;
int offset = 0;
for (int len : ranks) {
auto start_it = shape_concat.begin() + offset;
auto end_it = start_it + len;
res.push_back(framework::make_ddim(std::vector<int>(start_it, end_it)));
offset += len;
}
return res;
}
// general infershape for file readers
class CreateFileReaderInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"The output file reader should not be null.");
const auto shape_concat =
ctx->Attrs().Get<std::vector<int>>("shape_concat");
const auto ranks = ctx->Attrs().Get<std::vector<int>>("ranks");
std::vector<framework::DDim> shapes = RestoreShapes(shape_concat, ranks);
ctx->SetReaderDims("Out", shapes);
if (ctx->IsRuntime()) {
const auto lod_levels = ctx->Attrs().Get<std::vector<int>>("lod_levels");
PADDLE_ENFORCE_EQ(
lod_levels.size(), shapes.size(),
"The number of 'lod_levels'(%d) doesn't match the number "
"of 'shapes'(%d).",
lod_levels.size(), shapes.size());
framework::VarDesc* reader =
boost::get<framework::VarDesc*>(ctx->GetOutputVarPtrs("Out")[0]);
reader->SetLoDLevels(lod_levels);
}
}
};
// general infershape for decorated readers
class CreateDecoratedReaderInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("UnderlyingReader"),
"Input(UnderlyingReader) should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"The output decorated reader should not be null.");
ctx->SetReaderDims("Out", ctx->GetReaderDims("UnderlyingReader"));
if (ctx->IsRuntime()) {
framework::VarDesc* in_reader = boost::get<framework::VarDesc*>(
ctx->GetInputVarPtrs("UnderlyingReader")[0]);
framework::VarDesc* out_reader =
boost::get<framework::VarDesc*>(ctx->GetOutputVarPtrs("Out")[0]);
out_reader->SetLoDLevels(in_reader->GetLoDLevels());
}
}
};
// general var type inference for file readers
class CreateFileReaderInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override {
std::string reader_name = op_desc.Output("Out")[0];
framework::VarDesc* reader = block->FindVarRecursive(reader_name);
reader->SetType(framework::proto::VarType::READER);
}
};
// general var type inference for decorated readers
class CreateDecoratedReaderInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override {
std::string in_reader_name = op_desc.Input("UnderlyingReader")[0];
framework::VarDesc* in_reader = block->FindVarRecursive(in_reader_name);
std::string out_reader_name = op_desc.Output("Out")[0];
framework::VarDesc* out_reader = block->FindVarRecursive(out_reader_name);
out_reader->SetType(framework::proto::VarType::READER);
out_reader->SetDataTypes(in_reader->GetDataTypes());
}
};
template <typename T>
class CreateRandomDataGeneratorOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& shape_concat = Attr<std::vector<int>>("shape_concat");
const auto& ranks = Attr<std::vector<int>>("ranks");
PADDLE_ENFORCE(!shape_concat.empty() && !ranks.empty());
PADDLE_ENFORCE_EQ(std::accumulate(ranks.begin(), ranks.end(), 0),
int(shape_concat.size()),
"The accumulate of all ranks should be equal to the "
"shape concat's length.");
std::vector<framework::DDim> shapes = RestoreShapes(shape_concat, ranks);
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(new framework::RandomDataGenerator<T>(shapes, Attr<float>("min"),
Attr<float>("max")));
}
};
class CreateRandomDataGeneratorOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
CreateRandomDataGeneratorOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
AddOutput("Out", "(ReaderHolder) The created random reader.");
AddAttr<std::vector<int>>("shape_concat",
"The concat of all data's shapes.");
AddAttr<std::vector<int>>(
"ranks",
"The ranks of each data."
"e.g."
"shape_concat = [2,3,4,5,6]"
"ranks = [3,2]"
"It means the reader will generate two data each time,"
"whose shapes are [2,3,4] and [5,6] respectively.");
AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
AddComment(R"DOC(
CreateRandomDataGenerator Operator
This Op creates a random reader.
The reader generates random data instead of really reading from files.
Generated data follow an uniform distribution between 'min' and 'max'.
)DOC");
}
};
class CreateShuffleReaderOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& underlying_reader = scope.FindVar(Input("UnderlyingReader"))
->Get<framework::ReaderHolder>();
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(new framework::ShuffleReader(underlying_reader.Get(),
Attr<int>("buffer_size")));
}
};
class CreateShuffleReaderOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CreateShuffleReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
AddInput(
"UnderlyingReader",
"(ReaderHolder) The underlying reader for creating a shuffle reader.");
AddOutput("Out", "(ReaderHolder) The created shuffle reader.");
AddAttr<int>("buffer_size", "The shuffle buffer size.").GreaterThan(0);
AddComment(R"DOC(
CreateShuffleReader Operator
A shuffle reader takes another reader as its 'underlying reader'
and yields the underlying reader's outputs in a shuffled order.
)DOC");
}
};
class CreateBatchReaderOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& underlying_reader = scope.FindVar(Input("UnderlyingReader"))
->Get<framework::ReaderHolder>();
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(new framework::BatchReader(underlying_reader.Get(),
Attr<int>("batch_size")));
}
};
class CreateBatchReaderOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CreateBatchReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
AddInput(
"UnderlyingReader",
"(ReaderHolder) The underlying reader for creating a batch reader.");
AddOutput("Out", "(ReaderHolder) The created batch reader.");
AddAttr<int>("batch_size",
"How many instances the batch reader yields each time.")
.GreaterThan(0);
AddComment(R"DOC(
CreateBatchReader Operator
A batch reader takes another reader as its 'underlying reader',
gathers the underlying reader's outputs and then yields them in batches.
)DOC");
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(create_random_data_generator,
ops::CreateRandomDataGeneratorOp<float>,
ops::CreateFileReaderInferShape,
ops::CreateRandomDataGeneratorOpMaker,
paddle::framework::EmptyGradOpMaker,
ops::CreateFileReaderInferVarType);
REGISTER_OPERATOR(create_shuffle_reader, ops::CreateShuffleReaderOp,
ops::CreateDecoratedReaderInferShape,
ops::CreateShuffleReaderOpMaker,
paddle::framework::EmptyGradOpMaker,
ops::CreateDecoratedReaderInferVarType);
REGISTER_OPERATOR(create_batch_reader, ops::CreateBatchReaderOp,
ops::CreateDecoratedReaderInferShape,
ops::CreateBatchReaderOpMaker,
paddle::framework::EmptyGradOpMaker,
ops::CreateDecoratedReaderInferVarType);
paddle/fluid/operators/detail/CMakeLists.txt
浏览文件 @ 42e65a20
grpc_library(sendrecvop_grpc SRCS sendrecvop_utils.cc grpc_client.cc grpc_server.cc PROTO send_recv.proto DEPS lod_tensor selected_rows)
if(WITH_DISTRIBUTE)
grpc_library(sendrecvop_grpc SRCS sendrecvop_utils.cc grpc_client.cc grpc_server.cc PROTO send_recv.proto DEPS lod_tensor selected_rows)
endif()
paddle/fluid/operators/reader/CMakeLists.txt 0 → 100644
浏览文件 @ 42e65a20
cc_library(reader_op_registry SRCS reader_op_registry.cc DEPS operator op_registry reader)
op_library(create_random_data_generator_op SRCS create_random_data_generator_op.cc DEPS reader_op_registry)
op_library(create_shuffle_reader_op SRCS create_shuffle_reader_op.cc DEPS reader_op_registry)
op_library(create_batch_reader_op SRCS create_batch_reader_op.cc DEPS reader_op_registry)
set(READER_LIBRARY create_random_data_generator_op create_shuffle_reader_op create_batch_reader_op PARENT_SCOPE)
paddle/fluid/operators/reader/create_batch_reader_op.cc 0 → 100644
浏览文件 @ 42e65a20
// 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/reader/reader_op_registry.h"
namespace paddle {
namespace operators {
namespace reader {
class BatchReader : public framework::DecoratedReader {
public:
BatchReader(ReaderBase* reader, int batch_size)
: DecoratedReader(reader), batch_size_(batch_size) {
buffer_.reserve(batch_size_);
}
void ReadNext(std::vector<framework::LoDTensor>* out) override;
private:
int batch_size_;
std::vector<std::vector<framework::LoDTensor>> buffer_;
};
class CreateBatchReaderOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& underlying_reader = scope.FindVar(Input("UnderlyingReader"))
->Get<framework::ReaderHolder>();
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(
new BatchReader(underlying_reader.Get(), Attr<int>("batch_size")));
}
};
class CreateBatchReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateBatchReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
AddAttr<int>("batch_size",
"How many instances the batch reader yields each time.")
.GreaterThan(0);
AddComment(R"DOC(
CreateBatchReader Operator
A batch reader takes another reader as its 'underlying reader',
gathers the underlying reader's outputs and then yields them in batches.
)DOC");
}
};
void BatchReader::ReadNext(std::vector<framework::LoDTensor>* out) {
buffer_.clear();
buffer_.reserve(batch_size_);
for (int i = 0; i < batch_size_; ++i) {
if (reader_->HasNext()) {
buffer_.push_back(std::vector<framework::LoDTensor>());
reader_->ReadNext(&buffer_.back());
} else {
break;
}
}
// Concat instances
out->clear();
if (buffer_.empty()) {
// if buffer_ is empty, the 'out' will return as an empty vector.
return;
}
int out_num = buffer_[0].size();
out->reserve(out_num);
for (int j = 0; j < out_num; ++j) {
// Merge shape and check date type
std::type_index batch_type = buffer_[0][j].type();
framework::DDim batch_shape = buffer_[0][j].dims();
for (size_t i = 1; i < buffer_.size(); ++i) {
std::type_index ins_type = buffer_[i][j].type();
framework::DDim ins_shape = buffer_[i][j].dims();
PADDLE_ENFORCE_EQ(batch_type, ins_type);
PADDLE_ENFORCE_EQ(slice_ddim(batch_shape, 1, batch_shape.size()),
slice_ddim(ins_shape, 1, ins_shape.size()));
PADDLE_ENFORCE_GT(ins_shape[0], 0);
batch_shape[0] += ins_shape[0];
}
framework::LoDTensor out_tensor;
out_tensor.Resize(batch_shape);
out_tensor.mutable_data(platform::CPUPlace(), batch_type);
int64_t dst_offset = 0;
// Merge lod and data
framework::LoD batch_lod;
for (size_t i = 0; i < buffer_.size(); ++i) {
framework::DDim ins_shape = buffer_[i][j].dims();
framework::LoD ins_lod = buffer_[i][j].lod();
if (i == 0) {
batch_lod = ins_lod;
} else {
PADDLE_ENFORCE_EQ(batch_lod.size(), ins_lod.size());
for (size_t level_idx = 0; level_idx < batch_lod.size(); ++level_idx) {
auto& lod_level = batch_lod[level_idx];
for (size_t k = 1; k < ins_lod[level_idx].size(); ++k) {
lod_level.push_back(ins_lod[level_idx][k] + lod_level.back());
}
}
}
auto dst = out_tensor.Slice(dst_offset, dst_offset + ins_shape[0]);
TensorCopy(buffer_[i][j], platform::CPUPlace(), &dst);
dst_offset += ins_shape[0];
}
out_tensor.set_lod(batch_lod);
out->push_back(out_tensor);
}
}
} // namespace reader
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators::reader;
REGISTER_DECORATED_READER_OPERATOR(create_batch_reader,
ops::CreateBatchReaderOp,
ops::CreateBatchReaderOpMaker);
paddle/fluid/operators/reader/create_random_data_generator_op.cc 0 → 100644
浏览文件 @ 42e65a20
// 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/reader/reader_op_registry.h"
namespace paddle {
namespace operators {
namespace reader {
template <typename T>
class RandomDataGenerator : public framework::FileReader {
public:
RandomDataGenerator(const std::vector<framework::DDim>& shapes, float min,
float max)
: FileReader(shapes), min_(min), max_(max) {
PADDLE_ENFORCE_LE(
min, max, "'min' shouldn't be greater than 'max'.(%f vs %f)", min, max);
unsigned int seed = std::random_device()();
engine_.seed(seed);
dist_ = std::uniform_real_distribution<float>(min_, max_);
}
void ReadNext(std::vector<framework::LoDTensor>* out) override {
out->clear();
out->reserve(shapes_.size());
for (const framework::DDim& shape : shapes_) {
PADDLE_ENFORCE_GE(
shape.size(), 2,
"The rank of reader's output data should be 2 at least.(Now it's %d)",
shape.size());
framework::LoDTensor out_tensor;
out_tensor.Resize(shape);
T* data = out_tensor.mutable_data<T>(platform::CPUPlace());
int64_t numel = framework::product(shape);
for (int64_t i = 0; i < numel; ++i) {
data[i] = dist_(engine_);
}
out->push_back(out_tensor);
}
}
bool HasNext() const override { return true; }
void ReInit() override { return; }
private:
float min_;
float max_;
std::minstd_rand engine_;
std::uniform_real_distribution<float> dist_;
};
template <typename T>
class CreateRandomDataGeneratorOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& shape_concat = Attr<std::vector<int>>("shape_concat");
const auto& ranks = Attr<std::vector<int>>("ranks");
PADDLE_ENFORCE(!shape_concat.empty() && !ranks.empty());
PADDLE_ENFORCE_EQ(std::accumulate(ranks.begin(), ranks.end(), 0),
int(shape_concat.size()),
"The accumulate of all ranks should be equal to the "
"shape concat's length.");
std::vector<framework::DDim> shapes = RestoreShapes(shape_concat, ranks);
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(new RandomDataGenerator<T>(shapes, Attr<float>("min"),
Attr<float>("max")));
}
};
class CreateRandomDataGeneratorOpMaker : public FileReaderMakerBase {
public:
CreateRandomDataGeneratorOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: FileReaderMakerBase(op_proto, op_checker) {
AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
AddComment(R"DOC(
CreateRandomDataGenerator Operator
This Op creates a random reader.
The reader generates random data instead of really reading from files.
Generated data follow an uniform distribution between 'min' and 'max'.
)DOC");
}
};
} // namespace reader
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators::reader;
REGISTER_FILE_READER_OPERATOR(create_random_data_generator,
ops::CreateRandomDataGeneratorOp<float>,
ops::CreateRandomDataGeneratorOpMaker);
paddle/fluid/operators/reader/create_shuffle_reader_op.cc 0 → 100644
浏览文件 @ 42e65a20
// 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/reader/reader_op_registry.h"
namespace paddle {
namespace operators {
namespace reader {
class ShuffleReader : public framework::DecoratedReader {
public:
ShuffleReader(ReaderBase* reader, int buffer_size)
: DecoratedReader(reader), buffer_size_(buffer_size), iteration_pos_(0) {
buffer_.reserve(buffer_size);
}
void ReadNext(std::vector<framework::LoDTensor>* out) override;
private:
int buffer_size_;
std::vector<std::vector<framework::LoDTensor>> buffer_;
size_t iteration_pos_;
};
void ShuffleReader::ReadNext(std::vector<framework::LoDTensor>* out) {
if (iteration_pos_ >= buffer_.size()) {
// Reload buffer with new data
buffer_.clear();
buffer_.reserve(buffer_size_);
for (int i = 0; i < buffer_size_; ++i) {
if (reader_->HasNext()) {
buffer_.push_back(std::vector<framework::LoDTensor>());
reader_->ReadNext(&buffer_.back());
} else {
break;
}
}
// TODO(fengjiayi): 'std::random_shuffle' can be very slow. It needs to be
// optimize.
std::random_shuffle(buffer_.begin(), buffer_.end());
iteration_pos_ = 0;
}
out->clear();
if (!buffer_.empty()) {
std::swap(*out, buffer_[iteration_pos_++]);
}
// if buffer_ is empty, the 'out' will return as an empty vector.
}
class CreateShuffleReaderOp : public framework::OperatorBase {
public:
using framework::OperatorBase::OperatorBase;
private:
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
const auto& underlying_reader = scope.FindVar(Input("UnderlyingReader"))
->Get<framework::ReaderHolder>();
auto* out = scope.FindVar(Output("Out"))
->template GetMutable<framework::ReaderHolder>();
out->Reset(
new ShuffleReader(underlying_reader.Get(), Attr<int>("buffer_size")));
}
};
class CreateShuffleReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateShuffleReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
AddAttr<int>("buffer_size", "The shuffle buffer size.").GreaterThan(0);
AddComment(R"DOC(
CreateShuffleReader Operator
A shuffle reader takes another reader as its 'underlying reader'
and yields the underlying reader's outputs in a shuffled order.
)DOC");
}
};
} // namespace reader
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators::reader;
REGISTER_DECORATED_READER_OPERATOR(create_shuffle_reader,
ops::CreateShuffleReaderOp,
ops::CreateShuffleReaderOpMaker);
paddle/fluid/operators/reader/reader_op_registry.cc 0 → 100644
浏览文件 @ 42e65a20
// 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 "reader_op_registry.h"
namespace paddle {
namespace operators {
namespace reader {
std::vector<framework::DDim> RestoreShapes(const std::vector<int>& shape_concat,
const std::vector<int>& ranks) {
std::vector<framework::DDim> res;
int offset = 0;
for (int len : ranks) {
auto start_it = shape_concat.begin() + offset;
auto end_it = start_it + len;
res.push_back(framework::make_ddim(std::vector<int>(start_it, end_it)));
offset += len;
}
return res;
}
FileReaderMakerBase::FileReaderMakerBase(
framework::OpProtoAndCheckerMaker::OpProto* op_proto,
framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
AddOutput("Out", "(ReaderHolder) The created random reader.");
AddAttr<std::vector<int>>("shape_concat", "The concat of all data's shapes.");
AddAttr<std::vector<int>>(
"ranks",
"The ranks of each data."
"e.g."
"shape_concat = [2,3,4,5,6]"
"ranks = [3,2]"
"It means the reader will generate two data each time,"
"whose shapes are [2,3,4] and [5,6] respectively.");
AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
}
void FileReaderInferShape::operator()(framework::InferShapeContext* ctx) const {
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"The output file reader should not be null.");
const auto shape_concat = ctx->Attrs().Get<std::vector<int>>("shape_concat");
const auto ranks = ctx->Attrs().Get<std::vector<int>>("ranks");
std::vector<framework::DDim> shapes = RestoreShapes(shape_concat, ranks);
ctx->SetReaderDims("Out", shapes);
if (ctx->IsRuntime()) {
const auto lod_levels = ctx->Attrs().Get<std::vector<int>>("lod_levels");
PADDLE_ENFORCE_EQ(lod_levels.size(), shapes.size(),
"The number of 'lod_levels'(%d) doesn't match the number "
"of 'shapes'(%d).",
lod_levels.size(), shapes.size());
framework::VarDesc* reader =
boost::get<framework::VarDesc*>(ctx->GetOutputVarPtrs("Out")[0]);
reader->SetLoDLevels(lod_levels);
}
}
void FileReaderInferVarType::operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const {
std::string reader_name = op_desc.Output("Out")[0];
framework::VarDesc* reader = block->FindVarRecursive(reader_name);
reader->SetType(framework::proto::VarType::READER);
}
void DecoratedReaderInferShape::operator()(
framework::InferShapeContext* ctx) const {
PADDLE_ENFORCE(ctx->HasInput("UnderlyingReader"),
"Input(UnderlyingReader) should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"The output decorated reader should not be null.");
ctx->SetReaderDims("Out", ctx->GetReaderDims("UnderlyingReader"));
if (ctx->IsRuntime()) {
framework::VarDesc* in_reader = boost::get<framework::VarDesc*>(
ctx->GetInputVarPtrs("UnderlyingReader")[0]);
framework::VarDesc* out_reader =
boost::get<framework::VarDesc*>(ctx->GetOutputVarPtrs("Out")[0]);
out_reader->SetLoDLevels(in_reader->GetLoDLevels());
}
}
void DecoratedReaderInferVarType::operator()(
const framework::OpDesc& op_desc, framework::BlockDesc* block) const {
std::string in_reader_name = op_desc.Input("UnderlyingReader")[0];
framework::VarDesc* in_reader = block->FindVarRecursive(in_reader_name);
std::string out_reader_name = op_desc.Output("Out")[0];
framework::VarDesc* out_reader = block->FindVarRecursive(out_reader_name);
out_reader->SetType(framework::proto::VarType::READER);
out_reader->SetDataTypes(in_reader->GetDataTypes());
}
DecoratedReaderMakerBase::DecoratedReaderMakerBase(
framework::OpProtoAndCheckerMaker::OpProto* op_proto,
framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
AddInput("UnderlyingReader",
"(ReaderHolder) The underlying reader for creating a batch reader.");
AddOutput("Out", "(ReaderHolder) The created batch reader.");
}
} // namespace reader
} // namespace operators
} // namespace paddle
paddle/fluid/operators/reader/reader_op_registry.h 0 → 100644
浏览文件 @ 42e65a20
// 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 "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
namespace paddle {
namespace operators {
namespace reader {
extern std::vector<framework::DDim> RestoreShapes(
const std::vector<int>& shape_concat, const std::vector<int>& ranks);
class FileReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
FileReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
};
class FileReaderInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext* ctx) const override;
};
class FileReaderInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override;
};
// general infershape for decorated reader
class DecoratedReaderInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext* ctx) const override;
};
// general var type inference for decorated reader
class DecoratedReaderInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override;
};
class DecoratedReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
DecoratedReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
};
} // namespace reader
} // namespace operators
} // namespace paddle
#define REGISTER_FILE_READER_OPERATOR(op_name, ...) \
REGISTER_OPERATOR(op_name, __VA_ARGS__, \
paddle::operators::reader::FileReaderInferShape, \
paddle::framework::EmptyGradOpMaker, \
paddle::operators::reader::FileReaderInferVarType)
#define REGISTER_DECORATED_READER_OPERATOR(op_name, ...) \
REGISTER_OPERATOR(op_name, __VA_ARGS__, \
paddle::operators::reader::DecoratedReaderInferShape, \
paddle::framework::EmptyGradOpMaker, \
paddle::operators::reader::DecoratedReaderInferVarType)
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