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

paddle/framework/CMakeLists.txt

@@ -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_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
-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_test(prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context)

paddle/framework/executor.cc

@@ -17,6 +17,7 @@ limitations under the License. */
 #include <set>
 
 #include "gflags/gflags.h"
+#include "paddle/framework/feed_fetch_method.h"
 #include "paddle/framework/feed_fetch_type.h"
 #include "paddle/framework/lod_rank_table.h"
 #include "paddle/framework/lod_tensor_array.h"
@@ -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 paddle

paddle/framework/executor.h

@@ -41,6 +41,12 @@ class Executor {
   void Run(const ProgramDesc&, Scope*, int, bool create_local_scope = 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:
   const platform::Place place_;
 };

paddle/framework/feed_fetch_method.cc

+/* 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

paddle/framework/feed_fetch_method.h

@@ -13,46 +13,18 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
-#include "glog/logging.h"
+
 #include "paddle/framework/feed_fetch_type.h"
 #include "paddle/framework/scope.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());
-}
+                     const std::string& var_name, size_t index);
 
 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;
-}
+                            size_t index);
 
 }  // namespace framework
 }  // namespace paddle

paddle/inference/inference.cc

@@ -15,7 +15,6 @@ limitations under the License. */
 #include "inference.h"
 #include <fstream>
 #include "paddle/framework/executor.h"
-#include "paddle/framework/feed_fetch_method.h"
 #include "paddle/framework/init.h"
 #include "paddle/framework/scope.h"
 
@@ -154,7 +153,7 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds,
     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.";
   }
 
@@ -165,19 +164,22 @@ void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds,
 
   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
   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
   fetchs.resize(fetch_var_names_.size());
   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 scope;
   delete executor;

paddle/pybind/CMakeLists.txt

 if(WITH_PYTHON)
   cc_library(paddle_pybind SHARED
     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})
   if(NOT APPLE AND NOT ANDROID)
     target_link_libraries(paddle_pybind rt)

paddle/pybind/pybind.cc

@@ -424,7 +424,9 @@ All parameter, weight, gradient are variables in Paddle.
 
   py::class_<framework::Executor>(m, "Executor")
       .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("init_gflags", framework::InitGflags);