未验证 提交 8f6c0a0f 编写于 作者: Y Yu Yang 提交者: GitHub

Extract InferShape to many cc files (#5174)

* Shrink Operator.h

* Fix CI compile
上级 5906baa3
......@@ -24,9 +24,10 @@ cc_test(program_desc_test SRCS program_desc_test.cc DEPS proto_desc)
cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute)
cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog)
cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute)
cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog shape_inference)
cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry)
cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS attribute ddim op_info operator glog)
cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog)
cc_library(op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator glog proto_desc)
cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)
......
......@@ -16,15 +16,51 @@ limitations under the License. */
#include <functional>
#include <mutex>
#include <unordered_map>
#include "glog/logging.h"
#include "paddle/framework/block_desc.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/program_desc.h"
#include "glog/logging.h"
#include "paddle/framework/shape_inference.h"
namespace paddle {
namespace framework {
class OpDescBind;
class BlockDescBind;
class CompileTimeInferShapeContext : public InferShapeContext {
public:
CompileTimeInferShapeContext(const OpDescBind &op,
const BlockDescBind &block);
bool HasInput(const std::string &name) const override;
bool HasOutput(const std::string &name) const override;
bool HasInputs(const std::string &name) const override;
bool HasOutputs(const std::string &name) const override;
DDim GetInputDim(const std::string &name) const override;
void SetOutputDim(const std::string &name, const DDim &dim) override;
AttrReader Attrs() const override;
const std::vector<std::string> &Inputs(
const std::string &name) const override;
const std::vector<std::string> &Outputs(
const std::string &name) const override;
private:
DDim GetDim(const std::string &name) const override;
void SetDim(const std::string &name, const DDim &dim) override;
const OpDescBind &op_;
const BlockDescBind &block_;
};
OpDescBind::OpDescBind(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs,
const AttributeMap &attrs) {
......@@ -288,5 +324,97 @@ void OpDescBind::InferVarType(BlockDescBind *block) const {
}
}
CompileTimeInferShapeContext::CompileTimeInferShapeContext(
const OpDescBind &op, const BlockDescBind &block)
: op_(op), block_(block) {}
bool CompileTimeInferShapeContext::HasInput(const std::string &name) const {
const std::vector<std::string> &input_names = op_.Input(name);
auto length = input_names.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL,
"Input(%s) should have only one value, "
"but it have %d now",
name, length);
return block_.HasVarRecursive(input_names[0]);
}
bool CompileTimeInferShapeContext::HasOutput(const std::string &name) const {
const std::vector<std::string> &output_names = op_.Output(name);
auto length = output_names.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL,
"Output(%s) should have only one value, "
"but it have %d now",
name, length);
return block_.HasVarRecursive(output_names[0]);
}
bool CompileTimeInferShapeContext::HasInputs(const std::string &name) const {
const std::vector<std::string> &input_names = op_.Input(name);
if (input_names.empty()) {
return false;
}
for (auto &input : input_names) {
if (!block_.HasVarRecursive(input)) return false;
}
return true;
}
bool CompileTimeInferShapeContext::HasOutputs(const std::string &name) const {
const std::vector<std::string> &output_names = op_.Output(name);
if (output_names.empty()) {
return false;
}
for (auto &output : output_names) {
if (!block_.HasVarRecursive(output)) return false;
}
return true;
}
DDim CompileTimeInferShapeContext::GetInputDim(const std::string &name) const {
std::vector<DDim> ddims = GetInputsDim(name);
auto length = ddims.size();
PADDLE_ENFORCE_EQ(length, 1UL,
"Input(%s) should have 1 value, "
"but it has %d now",
name, length);
return ddims[0];
}
void CompileTimeInferShapeContext::SetOutputDim(const std::string &name,
const DDim &dim) {
SetOutputsDim(name, {dim});
}
AttrReader CompileTimeInferShapeContext::Attrs() const {
return AttrReader(op_.GetAttrMap());
}
const std::vector<std::string> &CompileTimeInferShapeContext::Inputs(
const std::string &name) const {
return op_.Input(name);
}
const std::vector<std::string> &CompileTimeInferShapeContext::Outputs(
const std::string &name) const {
return op_.Output(name);
}
DDim CompileTimeInferShapeContext::GetDim(const std::string &name) const {
auto var = block_.FindVarRecursive(name);
PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
return framework::make_ddim(var->Shape());
}
void CompileTimeInferShapeContext::SetDim(const std::string &name,
const DDim &dim) {
block_.FindVarRecursive(name)->SetShape(framework::vectorize(dim));
}
} // namespace framework
} // namespace paddle
......@@ -29,6 +29,7 @@ limitations under the License. */
#include "paddle/framework/op_desc.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/scope.h"
#include "paddle/framework/shape_inference.h"
namespace paddle {
namespace framework {
......
......@@ -15,6 +15,7 @@ limitations under the License. */
#include "paddle/framework/operator.h"
#include <algorithm>
#include <atomic>
#include "paddle/framework/shape_inference.h"
namespace paddle {
namespace framework {
......@@ -273,5 +274,136 @@ bool OpSupportGPU(const std::string& op_type) {
return false;
}
class RuntimeInferShapeContext : public InferShapeContext {
public:
RuntimeInferShapeContext(const OperatorBase& op, const Scope& scope)
: op_(op), scope_(scope) {}
bool HasInput(const std::string& name) const override {
auto& ins = Inputs(name);
size_t length = ins.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL, "Input %s should have more than one inputs",
name);
auto ipt = ins[0];
auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
return var != nullptr;
}
bool HasOutput(const std::string& name) const override {
auto& outs = Outputs(name);
size_t length = outs.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL, "Output %s should have more than one inputs",
name);
auto ipt = outs[0];
auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
return var != nullptr;
}
bool HasInputs(const std::string& name) const override {
auto inputs = op_.Inputs(name);
if (inputs.empty()) {
return false;
}
for (auto& input : inputs) {
if (scope_.FindVar(input) == nullptr) {
return false;
}
}
return true;
}
bool HasOutputs(const std::string& name) const override {
auto outputs = op_.Outputs(name);
if (outputs.empty()) {
return false;
}
for (auto& output : outputs) {
if (scope_.FindVar(output) == nullptr) {
return false;
}
}
return true;
}
DDim GetInputDim(const std::string& name) const override {
return GetDim(op_.Input(name));
}
void SetOutputDim(const std::string& name, const DDim& dim) override {
SetDim(op_.Output(name), dim);
}
AttrReader Attrs() const override { return AttrReader(op_.Attrs()); }
const std::vector<std::string>& Inputs(
const std::string& name) const override {
return op_.Inputs(name);
}
const std::vector<std::string>& Outputs(
const std::string& name) const override {
return op_.Outputs(name);
}
private:
DDim GetDim(const std::string& name) const override {
Variable* var = scope_.FindVar(name);
if (var->IsType<LoDTensor>()) {
return var->Get<LoDTensor>().dims();
} else if (var->IsType<SelectedRows>()) {
return var->Get<SelectedRows>().GetCompleteDims();
} else {
PADDLE_THROW("Variable type must be LoDTensor/SelectedRows.");
}
}
void SetDim(const std::string& name, const DDim& dim) override {
Variable* var = scope_.FindVar(name);
if (var->IsType<LoDTensor>()) {
var->GetMutable<LoDTensor>()->Resize(dim);
} else if (var->IsType<SelectedRows>()) {
var->GetMutable<SelectedRows>()->set_height(dim[0]);
} else {
PADDLE_THROW("Variable type must be LoDTensor/SelectedRows.");
}
}
const OperatorBase& op_;
const Scope& scope_;
};
void OperatorWithKernel::Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const {
VLOG(3) << "Running operator " << this->Type();
RuntimeInferShapeContext infer_shape_ctx(*this, scope);
this->InferShape(&infer_shape_ctx);
ExecutionContext ctx(*this, scope, dev_ctx);
// check if op[type] has kernel registered.
auto& all_op_kernels = AllOpKernels();
auto kernels_iter = all_op_kernels.find(type_);
if (kernels_iter == all_op_kernels.end()) {
PADDLE_THROW("op[%s] has no kernel", type_);
}
// check if op[type] have kernel for kernel_key
OpKernelMap& kernels = kernels_iter->second;
auto kernel_key = OpKernelKey(IndicateDataType(ctx), dev_ctx);
auto kernel_iter = kernels.find(kernel_key);
if (kernel_iter == kernels.end()) {
PADDLE_THROW("op[%s] has no kernel with kernel_key[%s]", type_, kernel_key);
}
kernel_iter->second->Compute(ctx);
}
} // namespace framework
} // namespace paddle
......@@ -29,7 +29,6 @@ limitations under the License. */
#include "paddle/framework/op_info.h"
#include "paddle/framework/scope.h"
#include "paddle/framework/selected_rows.h"
#include "paddle/framework/shape_inference.h"
#include "paddle/framework/tensor.h"
#include "paddle/platform/device_context.h"
#include "paddle/platform/place.h"
......@@ -317,226 +316,6 @@ template <>
std::vector<Tensor*> ExecutionContext::MultiOutput<Tensor>(
const std::string& name) const;
class CompileTimeInferShapeContext : public InferShapeContext {
public:
CompileTimeInferShapeContext(const OpDescBind& op, const BlockDescBind& block)
: op_(op), block_(block) {}
bool HasInput(const std::string& name) const override {
const std::vector<std::string>& input_names = op_.Input(name);
auto length = input_names.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL,
"Input(%s) should have only one value, "
"but it have %d now",
name, length);
return block_.HasVarRecursive(input_names[0]);
}
bool HasOutput(const std::string& name) const override {
const std::vector<std::string>& output_names = op_.Output(name);
auto length = output_names.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL,
"Output(%s) should have only one value, "
"but it have %d now",
name, length);
return block_.HasVarRecursive(output_names[0]);
}
bool HasInputs(const std::string& name) const override {
const std::vector<std::string>& input_names = op_.Input(name);
if (input_names.empty()) {
return false;
}
for (auto& input : input_names) {
if (!block_.HasVarRecursive(input)) return false;
}
return true;
}
bool HasOutputs(const std::string& name) const override {
const std::vector<std::string>& output_names = op_.Output(name);
if (output_names.empty()) {
return false;
}
for (auto& output : output_names) {
if (!block_.HasVarRecursive(output)) return false;
}
return true;
}
DDim GetInputDim(const std::string& name) const override {
std::vector<DDim> ddims = GetInputsDim(name);
auto length = ddims.size();
PADDLE_ENFORCE_EQ(length, 1UL,
"Input(%s) should have 1 value, "
"but it has %d now",
name, length);
return ddims[0];
}
void SetInputDim(const std::string& name, const DDim& dim) override {
SetInputsDim(name, {dim});
}
DDim GetOutputDim(const std::string& name) const override {
std::vector<DDim> ddims = GetOutputsDim(name);
auto length = ddims.size();
PADDLE_ENFORCE_EQ(length, 1UL,
"Output(%s) should have 1 value, "
"but it has %d now",
name, length);
return ddims[0];
}
void SetOutputDim(const std::string& name, const DDim& dim) override {
SetOutputsDim(name, {dim});
}
AttrReader Attrs() const override { return AttrReader(op_.GetAttrMap()); }
const std::vector<std::string>& Inputs(
const std::string& name) const override {
return op_.Input(name);
}
const std::vector<std::string>& Outputs(
const std::string& name) const override {
return op_.Output(name);
}
private:
DDim GetDim(const std::string& name) const override {
auto var = block_.FindVarRecursive(name);
PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
return framework::make_ddim(var->Shape());
}
void SetDim(const std::string& name, const DDim& dim) override {
block_.FindVarRecursive(name)->SetShape(framework::vectorize(dim));
}
const OpDescBind& op_;
const BlockDescBind& block_;
};
class RuntimeInferShapeContext : public InferShapeContext {
public:
RuntimeInferShapeContext(const OperatorBase& op, const Scope& scope)
: op_(op), scope_(scope) {}
bool HasInput(const std::string& name) const override {
auto& ins = Inputs(name);
size_t length = ins.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL, "Input %s should have more than one inputs",
name);
auto ipt = ins[0];
auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
return var != nullptr;
}
bool HasOutput(const std::string& name) const override {
auto& outs = Outputs(name);
size_t length = outs.size();
if (length == 0) {
return false;
}
PADDLE_ENFORCE_EQ(length, 1UL, "Output %s should have more than one inputs",
name);
auto ipt = outs[0];
auto* var = ipt == kEmptyVarName ? nullptr : scope_.FindVar(ipt);
return var != nullptr;
}
bool HasInputs(const std::string& name) const override {
auto inputs = op_.Inputs(name);
if (inputs.empty()) {
return false;
}
for (auto& input : inputs) {
if (scope_.FindVar(input) == nullptr) {
return false;
}
}
return true;
}
bool HasOutputs(const std::string& name) const override {
auto outputs = op_.Outputs(name);
if (outputs.empty()) {
return false;
}
for (auto& output : outputs) {
if (scope_.FindVar(output) == nullptr) {
return false;
}
}
return true;
}
DDim GetInputDim(const std::string& name) const override {
return GetDim(op_.Input(name));
}
void SetInputDim(const std::string& name, const DDim& dim) override {
SetDim(op_.Input(name), dim);
}
DDim GetOutputDim(const std::string& name) const override {
return GetDim(op_.Output(name));
}
void SetOutputDim(const std::string& name, const DDim& dim) override {
SetDim(op_.Output(name), dim);
}
AttrReader Attrs() const override { return AttrReader(op_.Attrs()); }
const std::vector<std::string>& Inputs(
const std::string& name) const override {
return op_.Inputs(name);
}
const std::vector<std::string>& Outputs(
const std::string& name) const override {
return op_.Outputs(name);
}
private:
DDim GetDim(const std::string& name) const override {
Variable* var = scope_.FindVar(name);
if (var->IsType<LoDTensor>()) {
return var->Get<LoDTensor>().dims();
} else if (var->IsType<SelectedRows>()) {
return var->Get<SelectedRows>().GetCompleteDims();
} else {
PADDLE_THROW("Variable type must be LoDTensor/SelectedRows.");
}
}
void SetDim(const std::string& name, const DDim& dim) override {
Variable* var = scope_.FindVar(name);
if (var->IsType<LoDTensor>()) {
var->GetMutable<LoDTensor>()->Resize(dim);
} else if (var->IsType<SelectedRows>()) {
var->GetMutable<SelectedRows>()->set_height(dim[0]);
} else {
PADDLE_THROW("Variable type must be LoDTensor/SelectedRows.");
}
}
const OperatorBase& op_;
const Scope& scope_;
};
class OpKernelBase {
public:
/**
......@@ -595,32 +374,7 @@ class OperatorWithKernel : public OperatorBase {
: OperatorBase(type, inputs, outputs, attrs) {}
void Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const final {
VLOG(3) << "Running operator " << this->Type();
RuntimeInferShapeContext infer_shape_ctx(*this, scope);
this->InferShape(&infer_shape_ctx);
ExecutionContext ctx(*this, scope, dev_ctx);
// check if op[type] has kernel registered.
auto& all_op_kernels = AllOpKernels();
auto kernels_iter = all_op_kernels.find(type_);
if (kernels_iter == all_op_kernels.end()) {
PADDLE_THROW("op[%s] has no kernel", type_);
}
// check if op[type] have kernel for kernel_key
OpKernelMap& kernels = kernels_iter->second;
auto kernel_key = OpKernelKey(IndicateDataType(ctx), dev_ctx);
auto kernel_iter = kernels.find(kernel_key);
if (kernel_iter == kernels.end()) {
PADDLE_THROW("op[%s] has no kernel with kernel_key[%s]", type_,
kernel_key);
}
kernel_iter->second->Compute(ctx);
}
const platform::DeviceContext& dev_ctx) const final;
static std::unordered_map<std::string /* op_type */, OpKernelMap>&
AllOpKernels() {
......
/* 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/framework/shape_inference.h"
namespace paddle {
namespace framework {
std::vector<framework::DDim> InferShapeContext::GetInputsDim(
const std::string &name) const {
const std::vector<std::string> &names = Inputs(name);
return GetDims(names);
}
void InferShapeContext::SetOutputsDim(
const std::string &name, const std::vector<framework::DDim> &dims) {
auto &names = Outputs(name);
SetDims(names, dims);
}
void InferShapeContext::ShareLoD(const std::string &in, const std::string &out,
size_t i, size_t j) const {}
std::vector<framework::DDim> InferShapeContext::GetDims(
const std::vector<std::string> &names) const {
std::vector<framework::DDim> ret;
ret.reserve(names.size());
std::transform(
names.begin(), names.end(), std::back_inserter(ret),
[this](const std::string &name) { return this->GetDim(name); });
return ret;
}
void InferShapeContext::SetDims(const std::vector<std::string> &names,
const std::vector<framework::DDim> &dims) {
size_t length = names.size();
PADDLE_ENFORCE_EQ(length, dims.size());
for (size_t i = 0; i < length; ++i) {
SetDim(names[i], dims[i]);
}
}
} // namespace framework
} // namespace paddle
......@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include "paddle/framework/attribute.h"
#include "paddle/framework/ddim.h"
namespace paddle {
......@@ -21,7 +22,7 @@ namespace framework {
class InferShapeContext {
public:
virtual ~InferShapeContext() {}
virtual ~InferShapeContext() = default;
virtual bool HasInput(const std::string &name) const = 0;
virtual bool HasOutput(const std::string &name) const = 0;
......@@ -29,57 +30,32 @@ class InferShapeContext {
virtual bool HasOutputs(const std::string &name) const = 0;
virtual framework::DDim GetInputDim(const std::string &name) const = 0;
std::vector<framework::DDim> GetInputsDim(const std::string &name) const {
const std::vector<std::string> &names = Inputs(name);
return GetDims(names);
}
virtual void SetInputDim(const std::string &name,
const framework::DDim &dim) = 0;
void SetInputsDim(const std::string &name,
const std::vector<framework::DDim> &dims) {
auto &names = Inputs(name);
SetDims(names, dims);
}
virtual framework::DDim GetOutputDim(const std::string &name) const = 0;
std::vector<framework::DDim> GetOutputsDim(const std::string &name) const {
const std::vector<std::string> &names = Outputs(name);
return GetDims(names);
}
std::vector<framework::DDim> GetInputsDim(const std::string &name) const;
virtual void SetOutputDim(const std::string &name, const DDim &dim) = 0;
void SetOutputsDim(const std::string &name,
const std::vector<framework::DDim> &dims) {
auto &names = Outputs(name);
SetDims(names, dims);
}
const std::vector<framework::DDim> &dims);
virtual AttrReader Attrs() const = 0;
virtual const std::vector<std::string> &Inputs(
const std::string &name) const = 0;
virtual const std::vector<std::string> &Outputs(
const std::string &name) const = 0;
// TODO(qiao) implement this function
void ShareLoD(const std::string &in, const std::string &out, size_t i = 0,
size_t j = 0) const {}
size_t j = 0) const;
protected:
virtual framework::DDim GetDim(const std::string &name) const = 0;
virtual void SetDim(const std::string &name, const framework::DDim &dim) = 0;
std::vector<framework::DDim> GetDims(
const std::vector<std::string> &names) const {
std::vector<framework::DDim> ret;
ret.reserve(names.size());
std::transform(
names.begin(), names.end(), std::back_inserter(ret),
[this](const std::string &name) { return this->GetDim(name); });
return ret;
}
const std::vector<std::string> &names) const;
void SetDims(const std::vector<std::string> &names,
const std::vector<framework::DDim> &dims) {
size_t length = names.size();
PADDLE_ENFORCE_EQ(length, dims.size());
for (size_t i = 0; i < length; ++i) {
SetDim(names[i], dims[i]);
}
}
const std::vector<framework::DDim> &dims);
};
} // namespace framework
......
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