未验证 提交 788f5c6d 编写于 作者: K kexinzhao 提交者: GitHub

New Run() method for framework::Executor (#7807)

* initial commit

* add new executor run function

* fix bug

* fix multiple definition of feed_fetch_method issue

* fix cmake

* fix tensor copy error

* refine executor code

* add comments

* temporary modification

* address comments

* fix bug
上级 7333df85
...@@ -74,8 +74,10 @@ cc_library(backward SRCS backward.cc DEPS net_op) ...@@ -74,8 +74,10 @@ cc_library(backward SRCS backward.cc DEPS net_op)
cc_test(backward_test SRCS backward_test.cc DEPS backward recurrent_op device_context fill_constant_op) cc_test(backward_test SRCS backward_test.cc DEPS backward recurrent_op device_context fill_constant_op)
cc_library(lod_rank_table SRCS lod_rank_table.cc DEPS lod_tensor) cc_library(lod_rank_table SRCS lod_rank_table.cc DEPS lod_tensor)
cc_library(feed_fetch_method SRCS feed_fetch_method.cc DEPS lod_tensor scope glog)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope cc_library(executor SRCS executor.cc DEPS op_registry device_context scope
framework_proto backward glog lod_rank_table profiler) framework_proto backward glog lod_rank_table profiler feed_fetch_method)
cc_library(prune SRCS prune.cc DEPS framework_proto) cc_library(prune SRCS prune.cc DEPS framework_proto)
cc_test(prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context) cc_test(prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context)
......
...@@ -17,6 +17,7 @@ limitations under the License. */ ...@@ -17,6 +17,7 @@ limitations under the License. */
#include <set> #include <set>
#include "gflags/gflags.h" #include "gflags/gflags.h"
#include "paddle/framework/feed_fetch_method.h"
#include "paddle/framework/feed_fetch_type.h" #include "paddle/framework/feed_fetch_type.h"
#include "paddle/framework/lod_rank_table.h" #include "paddle/framework/lod_rank_table.h"
#include "paddle/framework/lod_tensor_array.h" #include "paddle/framework/lod_tensor_array.h"
...@@ -149,5 +150,168 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id, ...@@ -149,5 +150,168 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id,
} }
} }
// Check whether the block already has feed operators and feed_holder.
// Return false if the block does not have any feed operators.
// If some feed operators have been prepended to the block, check that
// the info contained in these feed operators matches the feed_targets
// and feed_holder_name. Raise exception when any mismatch is found.
// Return true if the block has feed operators and holder of matching info.
static bool has_feed_operators(
BlockDesc* block, std::map<std::string, const LoDTensor*>& feed_targets,
const std::string& feed_holder_name) {
size_t feed_count = 0;
for (auto* op : block->AllOps()) {
if (op->Type() == kFeedOpType) {
feed_count++;
PADDLE_ENFORCE_EQ(op->Input("X")[0], feed_holder_name,
"Input to feed op should be '%s'", feed_holder_name);
std::string feed_target_name = op->Output("Out")[0];
PADDLE_ENFORCE(
feed_targets.find(feed_target_name) != feed_targets.end(),
"Feed operator output name '%s' cannot be found in 'feed_targets'",
feed_target_name);
} else {
break;
}
}
if (feed_count > 0) {
PADDLE_ENFORCE_EQ(
feed_count, feed_targets.size(),
"The number of feed operators should match 'feed_targets'");
// When feed operator are present, so should be feed_holder
auto var = block->FindVar(feed_holder_name);
PADDLE_ENFORCE_NOT_NULL(var, "Block should already have a '%s' variable",
feed_holder_name);
PADDLE_ENFORCE_EQ(var->GetType(), proto::VarDesc::FEED_MINIBATCH,
"'%s' variable should be 'FEED_MINIBATCH' type",
feed_holder_name);
}
return feed_count > 0;
}
// Check whether the block already has fetch operators and fetch_holder.
// Return false if the block does not have any fetch operators.
// If some fetch operators have been appended to the block, check that
// the info contained in these fetch operators matches the fetch_targets
// and fetch_holder_name. Raise exception when any mismatch is found.
// Return true if the block has fetch operators and holder of matching info.
static bool has_fetch_operators(
BlockDesc* block, std::map<std::string, LoDTensor*>& fetch_targets,
const std::string& fetch_holder_name) {
size_t fetch_count = 0;
for (auto* op : block->AllOps()) {
if (op->Type() == kFetchOpType) {
fetch_count++;
PADDLE_ENFORCE_EQ(op->Output("Out")[0], fetch_holder_name,
"Output of fetch op should be '%s'", fetch_holder_name);
std::string fetch_target_name = op->Input("X")[0];
PADDLE_ENFORCE(
fetch_targets.find(fetch_target_name) != fetch_targets.end(),
"Fetch operator input name '%s' cannot be found in 'fetch_targets'",
fetch_target_name);
}
}
if (fetch_count > 0) {
PADDLE_ENFORCE_EQ(
fetch_count, fetch_targets.size(),
"The number of fetch operators should match 'fetch_targets'");
// When fetch operator are present, so should be fetch_holder
auto var = block->FindVar(fetch_holder_name);
PADDLE_ENFORCE_NOT_NULL(var, "Block should already have a '%s' variable",
fetch_holder_name);
PADDLE_ENFORCE_EQ(var->GetType(), proto::VarDesc::FETCH_LIST,
"'%s' variable should be 'FETCH_LIST' type",
fetch_holder_name);
}
return fetch_count > 0;
}
void Executor::Run(const ProgramDesc& program, Scope* scope,
std::map<std::string, const LoDTensor*>& feed_targets,
std::map<std::string, LoDTensor*>& fetch_targets,
const std::string& feed_holder_name,
const std::string& fetch_holder_name) {
auto* copy_program = new ProgramDesc(program);
auto* global_block = copy_program->MutableBlock(0);
if (!has_feed_operators(global_block, feed_targets, feed_holder_name)) {
// create feed_holder variable
auto* feed_holder = global_block->Var(feed_holder_name);
feed_holder->SetType(proto::VarDesc::FEED_MINIBATCH);
feed_holder->SetPersistable(true);
int i = 0;
for (auto& feed_target : feed_targets) {
std::string var_name = feed_target.first;
VLOG(3) << "feed target's name: " << var_name;
// prepend feed op
auto* op = global_block->PrependOp();
op->SetType(kFeedOpType);
op->SetInput("X", {feed_holder_name});
op->SetOutput("Out", {var_name});
op->SetAttr("col", {static_cast<int>(i)});
op->CheckAttrs();
i++;
}
}
// map the data of feed_targets to feed_holder
for (auto* op : global_block->AllOps()) {
if (op->Type() == kFeedOpType) {
std::string feed_target_name = op->Output("Out")[0];
int idx = boost::get<int>(op->GetAttr("col"));
SetFeedVariable(scope, *feed_targets[feed_target_name], feed_holder_name,
idx);
} else {
break;
}
}
if (!has_fetch_operators(global_block, fetch_targets, fetch_holder_name)) {
// create fetch_holder variable
auto* fetch_holder = global_block->Var(fetch_holder_name);
fetch_holder->SetType(proto::VarDesc::FETCH_LIST);
fetch_holder->SetPersistable(true);
int i = 0;
for (auto& fetch_target : fetch_targets) {
std::string var_name = fetch_target.first;
VLOG(3) << "fetch target's name: " << var_name;
// append fetch op
auto* op = global_block->AppendOp();
op->SetType(kFetchOpType);
op->SetInput("X", {var_name});
op->SetOutput("Out", {fetch_holder_name});
op->SetAttr("col", {static_cast<int>(i)});
op->CheckAttrs();
i++;
}
}
Run(*copy_program, scope, 0, true, true);
// obtain the data of fetch_targets from fetch_holder
for (auto* op : global_block->AllOps()) {
if (op->Type() == kFetchOpType) {
std::string fetch_target_name = op->Input("X")[0];
int idx = boost::get<int>(op->GetAttr("col"));
*fetch_targets[fetch_target_name] =
GetFetchVariable(*scope, fetch_holder_name, idx);
}
}
delete copy_program;
}
} // namespace framework } // namespace framework
} // namespace paddle } // namespace paddle
...@@ -41,6 +41,12 @@ class Executor { ...@@ -41,6 +41,12 @@ class Executor {
void Run(const ProgramDesc&, Scope*, int, bool create_local_scope = true, void Run(const ProgramDesc&, Scope*, int, bool create_local_scope = true,
bool create_vars = true); bool create_vars = true);
void Run(const ProgramDesc& program, Scope* scope,
std::map<std::string, const LoDTensor*>& feed_targets,
std::map<std::string, LoDTensor*>& fetch_targets,
const std::string& feed_holder_name = "feed",
const std::string& fetch_holder_name = "fetch");
private: private:
const platform::Place place_; const platform::Place place_;
}; };
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/feed_fetch_method.h"
#include "glog/logging.h"
#include "paddle/framework/variable.h"
namespace paddle {
namespace framework {
void SetFeedVariable(Scope* scope, const LoDTensor& input,
const std::string& var_name, size_t index) {
// If var_name Variable is not found in GlobalScope, a new variable will
// be created.
VLOG(3) << "SetFeedVariable name=" << var_name << " index=" << index;
Variable* g_feed_value = scope->Var(var_name);
auto& feed_inputs =
*(g_feed_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
if (index >= feed_inputs.size()) {
feed_inputs.resize(index + 1);
}
// shared data with input tensor
feed_inputs[index].ShareDataWith(input);
// set lod
feed_inputs[index].set_lod(input.lod());
}
LoDTensor& GetFetchVariable(const Scope& scope, const std::string& var_name,
size_t index) {
// Since we want to fetch LodTensor from a variable, the variable must
// be created alreadly.
Variable* g_fetch_value = scope.FindVar(var_name);
PADDLE_ENFORCE(g_fetch_value->IsType<FeedFetchList>(),
"Only %s can be invoked by GetFetchVariable",
typeid(FeedFetchList).name());
auto& fetch_outputs = *g_fetch_value->GetMutable<FeedFetchList>();
auto& tensor = fetch_outputs[index];
VLOG(3) << "Fetch " << var_name << " with index " << index
<< " shape= " << tensor.dims();
PADDLE_ENFORCE_LT(index, fetch_outputs.size());
return tensor;
}
} // namespace framework
} // namespace paddle
...@@ -13,46 +13,18 @@ See the License for the specific language governing permissions and ...@@ -13,46 +13,18 @@ See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#pragma once #pragma once
#include "glog/logging.h"
#include "paddle/framework/feed_fetch_type.h" #include "paddle/framework/feed_fetch_type.h"
#include "paddle/framework/scope.h" #include "paddle/framework/scope.h"
#include "paddle/framework/variable.h"
namespace paddle { namespace paddle {
namespace framework { namespace framework {
void SetFeedVariable(Scope* scope, const LoDTensor& input, void SetFeedVariable(Scope* scope, const LoDTensor& input,
const std::string& var_name, size_t index) { const std::string& var_name, size_t index);
// If var_name Variable is not found in GlobalScope, a new variable will
// be created.
VLOG(3) << "SetFeedVariable name=" << var_name << " index=" << index;
Variable* g_feed_value = scope->Var(var_name);
auto& feed_inputs =
*(g_feed_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
if (index >= feed_inputs.size()) {
feed_inputs.resize(index + 1);
}
// shared data with input tensor
feed_inputs[index].ShareDataWith(input);
// set lod
feed_inputs[index].set_lod(input.lod());
}
LoDTensor& GetFetchVariable(const Scope& scope, const std::string& var_name, LoDTensor& GetFetchVariable(const Scope& scope, const std::string& var_name,
size_t index) { size_t index);
// Since we want to fetch LodTensor from a variable, the variable must
// be created alreadly.
Variable* g_fetch_value = scope.FindVar(var_name);
PADDLE_ENFORCE(g_fetch_value->IsType<FeedFetchList>(),
"Only %s can be invoked by GetFetchVariable",
typeid(FeedFetchList).name());
auto& fetch_outputs = *g_fetch_value->GetMutable<FeedFetchList>();
auto& tensor = fetch_outputs[index];
VLOG(3) << "Fetch " << var_name << " with index " << index
<< " shape= " << tensor.dims();
PADDLE_ENFORCE_LT(index, fetch_outputs.size());
return tensor;
}
} // namespace framework } // namespace framework
} // namespace paddle } // namespace paddle
...@@ -15,7 +15,6 @@ limitations under the License. */ ...@@ -15,7 +15,6 @@ limitations under the License. */
#include "inference.h" #include "inference.h"
#include <fstream> #include <fstream>
#include "paddle/framework/executor.h" #include "paddle/framework/executor.h"
#include "paddle/framework/feed_fetch_method.h"
#include "paddle/framework/init.h" #include "paddle/framework/init.h"
#include "paddle/framework/scope.h" #include "paddle/framework/scope.h"
...@@ -154,7 +153,7 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds, ...@@ -154,7 +153,7 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds,
LOG(FATAL) << "Please initialize the program_ and load_program_ first."; LOG(FATAL) << "Please initialize the program_ and load_program_ first.";
} }
if (feeds.size() < feed_var_names_.size()) { if (feeds.size() != feed_var_names_.size()) {
LOG(FATAL) << "Please feed " << feed_var_names_.size() << " input Tensors."; LOG(FATAL) << "Please feed " << feed_var_names_.size() << " input Tensors.";
} }
...@@ -165,19 +164,22 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds, ...@@ -165,19 +164,22 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds,
executor->Run(*load_program_, scope, 0, true, true); executor->Run(*load_program_, scope, 0, true, true);
std::map<std::string, const framework::LoDTensor*> feed_targets;
std::map<std::string, framework::LoDTensor*> fetch_targets;
// set_feed_variable // set_feed_variable
for (size_t i = 0; i < feed_var_names_.size(); ++i) { for (size_t i = 0; i < feed_var_names_.size(); ++i) {
framework::SetFeedVariable(scope, feeds[i], "feed", i); feed_targets[feed_var_names_[i]] = &feeds[i];
} }
executor->Run(*program_, scope, 0, true, true);
// get_fetch_variable // get_fetch_variable
fetchs.resize(fetch_var_names_.size()); fetchs.resize(fetch_var_names_.size());
for (size_t i = 0; i < fetch_var_names_.size(); ++i) { for (size_t i = 0; i < fetch_var_names_.size(); ++i) {
fetchs[i] = framework::GetFetchVariable(*scope, "fetch", i); fetch_targets[fetch_var_names_[i]] = &fetchs[i];
} }
executor->Run(*program_, scope, feed_targets, fetch_targets);
delete place; delete place;
delete scope; delete scope;
delete executor; delete executor;
......
if(WITH_PYTHON) if(WITH_PYTHON)
cc_library(paddle_pybind SHARED cc_library(paddle_pybind SHARED
SRCS pybind.cc exception.cc protobuf.cc const_value.cc SRCS pybind.cc exception.cc protobuf.cc const_value.cc
DEPS pybind python backward proto_desc paddle_memory executor prune init profiler DEPS pybind python backward proto_desc paddle_memory executor prune init profiler feed_fetch_method
${GLOB_OP_LIB}) ${GLOB_OP_LIB})
if(NOT APPLE AND NOT ANDROID) if(NOT APPLE AND NOT ANDROID)
target_link_libraries(paddle_pybind rt) target_link_libraries(paddle_pybind rt)
......
...@@ -424,7 +424,9 @@ All parameter, weight, gradient are variables in Paddle. ...@@ -424,7 +424,9 @@ All parameter, weight, gradient are variables in Paddle.
py::class_<framework::Executor>(m, "Executor") py::class_<framework::Executor>(m, "Executor")
.def(py::init<const platform::Place &>()) .def(py::init<const platform::Place &>())
.def("run", &Executor::Run); .def("run",
(void (Executor::*)(const ProgramDesc &, Scope *, int, bool, bool)) &
Executor::Run);
m.def("unique_integer", UniqueIntegerGenerator); m.def("unique_integer", UniqueIntegerGenerator);
m.def("init_gflags", framework::InitGflags); m.def("init_gflags", framework::InitGflags);
......
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