Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix_python35_CI_random_fail

doc/fluid/new_docs/user_guides/howto/debug/visualdl.md

@@ -104,6 +104,7 @@ visualDL --logdir=scratch_log --port=8080
 
 # 访问 http://127.0.0.1:8080
 ```
+如果出现`TypeError: __init__() got an unexpected keyword argument 'file'`, 是因为protobuf不是3.5以上，运行`pip install --upgrade protobuf`就能解决。
 
 如果在虚拟环境下仍然遇到安装问题，请尝试以下方法。
 

paddle/fluid/API.spec

@@ -43,6 +43,7 @@ paddle.fluid.Executor.run ArgSpec(args=['self', 'program', 'feed', 'fetch_list',
 paddle.fluid.global_scope ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
 paddle.fluid.scope_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
 paddle.fluid.Trainer.__init__ ArgSpec(args=['self', 'train_func', 'optimizer_func', 'param_path', 'place', 'parallel', 'checkpoint_config'], varargs=None, keywords=None, defaults=(None, None, False, None))
+paddle.fluid.Trainer.save_inference_model ArgSpec(args=['self', 'param_path', 'feeded_var_names', 'target_var_indexes'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.Trainer.save_params ArgSpec(args=['self', 'param_path'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.Trainer.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.Trainer.test ArgSpec(args=['self', 'reader', 'feed_order'], varargs=None, keywords=None, defaults=None)

paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc

@@ -11,6 +11,7 @@
 // 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/ir/fc_lstm_fuse_pass.h"
 #include <string>
 #include "paddle/fluid/framework/lod_tensor.h"

paddle/fluid/inference/analysis/CMakeLists.txt

@@ -6,6 +6,7 @@ cc_library(analysis SRCS pass_manager.cc node.cc data_flow_graph.cc graph_traits
   analyzer.cc
   helper.cc
   # passes
+  analysis_pass.cc
   fluid_to_data_flow_graph_pass.cc
   data_flow_graph_to_fluid_pass.cc
   dfg_graphviz_draw_pass.cc
@@ -105,6 +106,6 @@ if (NOT EXISTS ${TEXT_CLASSIFICATION_INSTALL_DIR} AND WITH_TESTING AND WITH_INFE
   inference_download_and_uncompress(${TEXT_CLASSIFICATION_INSTALL_DIR} ${TEXT_CLASSIFICATION_MODEL_URL} "text-classification-Senta.tar.gz")
 endif()
 
-inference_analysis_test(test_text_classification SRCS test_text_classification.cc
+inference_analysis_test(test_text_classification SRCS analyzer_text_classification_tester.cc
     EXTRA_DEPS paddle_inference_api paddle_fluid_api analysis_predictor
     ARGS --infer_model=${TEXT_CLASSIFICATION_INSTALL_DIR}/text-classification-Senta)

paddle/fluid/inference/analysis/pass.cc → paddle/fluid/inference/analysis/analysis_pass.cc

@@ -12,4 +12,4 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/fluid/inference/analysis/pass.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"

paddle/fluid/inference/analysis/pass.h → paddle/fluid/inference/analysis/analysis_pass.h

@@ -28,10 +28,10 @@ namespace paddle {
 namespace inference {
 namespace analysis {
 
-class Pass {
+class AnalysisPass {
  public:
-  Pass() = default;
-  virtual ~Pass() = default;
+  AnalysisPass() = default;
+  virtual ~AnalysisPass() = default;
   // Mutable Pass.
   virtual bool Initialize(Argument *argument) { return false; }
   // Readonly Pass.
@@ -42,23 +42,16 @@ class Pass {
   virtual bool Finalize() { return false; }
 
   // Get a Pass appropriate to print the Node this pass operates on.
-  virtual Pass *CreatePrinterPass(std::ostream &os,
-                                  const std::string &banner) const {
+  virtual AnalysisPass *CreatePrinterPass(std::ostream &os,
+                                          const std::string &banner) const {
     return nullptr;
   }
 
   // Create a debugger Pass that draw the DFG by graphviz toolkit.
-  virtual Pass *CreateGraphvizDebugerPass() const { return nullptr; }
+  virtual AnalysisPass *CreateGraphvizDebugerPass() const { return nullptr; }
 
-  virtual void Run() { LOG(FATAL) << "not valid"; }
-  // Run on a single Node.
-  virtual void Run(Node *x) { LOG(FATAL) << "not valid"; }
-  // Run on a single Function.
-  virtual void Run(Function *x) { LOG(FATAL) << "not valid"; }
-  // Run on a single FunctionBlock.
-  virtual void Run(FunctionBlock *x) { LOG(FATAL) << "not valid"; }
   // Run on a single DataFlowGraph.
-  virtual void Run(DataFlowGraph *x) { LOG(FATAL) << "not valid"; }
+  virtual void Run(DataFlowGraph *x) = 0;
 
   // Human-readable short representation.
   virtual std::string repr() const = 0;
@@ -66,29 +59,8 @@ class Pass {
   virtual std::string description() const { return "No DOC"; }
 };
 
-// NodePass process on any Node types.
-class NodePass : public Pass {
- public:
-  virtual void Run(Node *node) = 0;
-};
-
-// NodePass process on any Function node types.
-class FunctionPass : public Pass {
- public:
-  virtual void Run(Function *node) = 0;
-};
-
-// NodePass process on any FunctionBlock node types.
-class FunctionBlockPass : public Pass {
- public:
-  virtual void Run(FunctionBlock *node) = 0;
-};
-
 // GraphPass processes on any GraphType.
-class DataFlowGraphPass : public Pass {
- public:
-  virtual void Run(DataFlowGraph *graph) = 0;
-};
+class DataFlowGraphPass : public AnalysisPass {};
 
 }  // namespace analysis
 }  // namespace inference

paddle/fluid/inference/analysis/analyzer.cc

@@ -15,6 +15,7 @@
 #include "paddle/fluid/inference/analysis/analyzer.h"
 #include <string>
 #include <vector>
+
 #include "paddle/fluid/inference/analysis/data_flow_graph_to_fluid_pass.h"
 #include "paddle/fluid/inference/analysis/dfg_graphviz_draw_pass.h"
 #include "paddle/fluid/inference/analysis/fluid_to_data_flow_graph_pass.h"
@@ -58,7 +59,7 @@ class DfgPassManagerImpl final : public DfgPassManager {
   std::string description() const override { return "DFG pass manager."; }
 
  private:
-  void AddPass(const std::string& name, Pass* pass) {
+  void AddPass(const std::string& name, AnalysisPass* pass) {
     VLOG(3) << "Adding pass " << name;
     Register(name, pass);
     AddGraphvizDebugerPass(pass);
@@ -87,7 +88,7 @@ class DfgPassManagerImpl final : public DfgPassManager {
   }
 
   // Add the graphviz debuger pass if the parent pass has one.
-  void AddGraphvizDebugerPass(Pass* pass) {
+  void AddGraphvizDebugerPass(AnalysisPass* pass) {
     auto* debuger_pass = pass->CreateGraphvizDebugerPass();
     if (debuger_pass) {
       Register(debuger_pass->repr(), debuger_pass);

paddle/fluid/inference/analysis/analyzer.h

@@ -36,8 +36,11 @@ limitations under the License. */
  */
 
 #include <gflags/gflags.h>
+#include <string>
+#include <vector>
+
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/flags.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 #include "paddle/fluid/inference/analysis/pass_manager.h"
 
 namespace paddle {

paddle/fluid/inference/analysis/test_text_classification.cc → paddle/fluid/inference/analysis/analyzer_text_classification_tester.cc

@@ -12,13 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/inference/analysis/analyzer.h"
 #include <gflags/gflags.h>
 #include <glog/logging.h>  // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
 #include <gtest/gtest.h>
 #include "paddle/fluid/framework/ir/pass.h"
-#include "paddle/fluid/inference/analysis/analyzer.h"
 #include "paddle/fluid/inference/analysis/ut_helper.h"
 #include "paddle/fluid/inference/api/paddle_inference_api.h"
+#include "paddle/fluid/inference/api/paddle_inference_pass.h"
 #include "paddle/fluid/inference/api/timer.h"
 
 DEFINE_string(infer_model, "", "Directory of the inference model.");
@@ -100,10 +101,3 @@ void Main(int batch_size) {
 TEST(text_classification, basic) { Main(FLAGS_batch_size); }
 
 }  // namespace paddle
-
-USE_PASS(fc_fuse_pass);
-USE_PASS(seq_concat_fc_fuse_pass);
-USE_PASS(fc_lstm_fuse_pass);
-USE_PASS(graph_viz_pass);
-USE_PASS(infer_clean_graph_pass);
-USE_PASS(attention_lstm_fuse_pass);

paddle/fluid/inference/analysis/data_flow_graph_to_fluid_pass.cc

@@ -263,7 +263,7 @@ class DFG_DebuggerPass : public DFG_GraphvizDrawPass {
 };
 }  // namespace
 
-Pass *DataFlowGraphToFluidPass::CreateGraphvizDebugerPass() const {
+AnalysisPass *DataFlowGraphToFluidPass::CreateGraphvizDebugerPass() const {
   return new DFG_DebuggerPass(DFG_GraphvizDrawPass::Config(
       FLAGS_IA_graphviz_log_root,
       "data_flow_graph_to_fluid_graphviz_debugger"));

paddle/fluid/inference/analysis/data_flow_graph_to_fluid_pass.h

@@ -21,8 +21,8 @@
 
 #include <string>
 #include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/data_flow_graph.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 
 namespace paddle {
 namespace inference {
@@ -42,7 +42,7 @@ class DataFlowGraphToFluidPass final : public DataFlowGraphPass {
     return "Transform a DFG to a Fluid ProgramDesc";
   }
 
-  Pass *CreateGraphvizDebugerPass() const override;
+  AnalysisPass *CreateGraphvizDebugerPass() const override;
 
  protected:
   // Add a Fluid Op into the ProgramDesc.

paddle/fluid/inference/analysis/dfg_graphviz_draw_pass.h

@@ -21,8 +21,8 @@ limitations under the License. */
 
 #include <fstream>
 #include <string>
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/dot.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 
 namespace paddle {
 namespace inference {

paddle/fluid/inference/analysis/fluid_to_data_flow_graph_pass.cc

@@ -66,7 +66,7 @@ class DFG_DebuggerPass : public DFG_GraphvizDrawPass {
 };
 }
 
-Pass *FluidToDataFlowGraphPass::CreateGraphvizDebugerPass() const {
+AnalysisPass *FluidToDataFlowGraphPass::CreateGraphvizDebugerPass() const {
   return new DFG_DebuggerPass(DFG_GraphvizDrawPass::Config(
       FLAGS_IA_graphviz_log_root, "fluid-to-dfg-debuger"));
 }

paddle/fluid/inference/analysis/fluid_to_data_flow_graph_pass.h

@@ -22,8 +22,8 @@
 #include <string>
 
 #include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/data_flow_graph.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 
 namespace paddle {
 namespace inference {
@@ -46,7 +46,7 @@ class FluidToDataFlowGraphPass final : public DataFlowGraphPass {
     return "transform a fluid ProgramDesc to a data flow graph.";
   }
 
-  Pass *CreateGraphvizDebugerPass() const override;
+  AnalysisPass *CreateGraphvizDebugerPass() const override;
 
  private:
   framework::proto::ProgramDesc const *desc_;

paddle/fluid/inference/analysis/fluid_to_ir_pass.h

@@ -14,15 +14,17 @@
 
 #pragma once
 
+#include <string>
+#include <vector>
+
 #include "paddle/fluid/framework/ir/fuse_pass_base.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/flags.h"
 #include "paddle/fluid/inference/analysis/ir_pass_manager.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 
 namespace paddle {
 namespace inference {
 namespace analysis {
-using namespace framework;
 
 static const char kFluidToIrPassesAttr[] = "__fluid_to_ir_passes__";
 
@@ -48,7 +50,8 @@ class FluidToIrPass final : public DataFlowGraphPass {
     ANALYSIS_ARGUMENT_CHECK_FIELD(argument->fluid_model_program_path);
     // Load program.
     auto program = LoadProgramDesc(*argument->fluid_model_program_path);
-    argument->origin_program_desc.reset(new proto::ProgramDesc(program));
+    argument->origin_program_desc.reset(
+        new framework::proto::ProgramDesc(program));
     // Create main data flow graph.
     if (!argument->main_dfg) {
       argument->main_dfg.reset(new DataFlowGraph);
@@ -78,12 +81,13 @@ class FluidToIrPass final : public DataFlowGraphPass {
     IRPassManager ir_passes(argument_->Get<ProgramDesc>("ir_program_desc"),
                             nullptr);
     // Pass the scope from analysis to IR if needed.
-    if (argument_->Has(ir::kParamScopeAttr)) {
+    if (argument_->Has(framework::ir::kParamScopeAttr)) {
       // Here the address is passed, attention that IR doesn't own the scope, so
       // the real scope in analysis should live during the IR phase.
       ir_passes.graph().Set(
-          ir::kParamScopeAttr,
-          new Scope *(&argument_->Get<Scope>(ir::kParamScopeAttr)));
+          framework::ir::kParamScopeAttr,
+          new framework::Scope *(&argument_->Get<framework::Scope>(
+              framework::ir::kParamScopeAttr)));
     }
 
     if (FLAGS_IA_enable_ir) {
@@ -95,12 +99,12 @@ class FluidToIrPass final : public DataFlowGraphPass {
     PADDLE_ENFORCE(argument_->main_dfg.get());
     argument_->main_dfg->Build(ir_passes.graph());
     // inherit the arguments from ir.
-    if (ir_passes.graph().Has(ir::kFuseStatisAttr)) {
+    if (ir_passes.graph().Has(framework::ir::kFuseStatisAttr)) {
       argument_->Set(
-          ir::kFuseStatisAttr,
+          framework::ir::kFuseStatisAttr,
           new std::unordered_map<std::string, int>(
               ir_passes.graph().Get<std::unordered_map<std::string, int>>(
-                  ir::kFuseStatisAttr)));
+                  framework::ir::kFuseStatisAttr)));
     }
   }
 
@@ -112,7 +116,7 @@ class FluidToIrPass final : public DataFlowGraphPass {
 
  private:
   // Load parameters from a single file or from a directory.
-  bool LoadParams(Scope *scope, const std::string &dir,
+  bool LoadParams(framework::Scope *scope, const std::string &dir,
                   const std::string &prog_file, const std::string &param_file);
 
  private:

paddle/fluid/inference/analysis/model_store_pass.h

@@ -19,7 +19,7 @@
 
 #pragma once
 #include <string>
-#include "paddle/fluid/inference/analysis/pass.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 
 namespace paddle {
 namespace inference {

paddle/fluid/inference/analysis/pass_manager.cc

@@ -40,17 +40,6 @@ void DfgPassManager::RunAll() {
   }
 }
 
-void NodePassManager::RunAll() {
-  PADDLE_ENFORCE(argument_);
-  PADDLE_ENFORCE(argument_->main_dfg.get());
-  auto trait = GraphTraits<DataFlowGraph>(*argument_->main_dfg).nodes_in_DFS();
-  for (auto& node : trait) {
-    for (auto& pass : data_) {
-      pass->Run(&node);
-    }
-  }
-}
-
 }  // namespace analysis
 }  // namespace inference
 }  // namespace paddle

paddle/fluid/inference/analysis/pass_manager.h

@@ -33,7 +33,7 @@ limitations under the License. */
 
 #include <string>
 #include "paddle/fluid/framework/program_desc.h"
-#include "paddle/fluid/inference/analysis/pass.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 
 namespace paddle {
 namespace inference {
@@ -43,7 +43,7 @@ namespace analysis {
  * PassManager is the base class for all pass managers, a pass manager has
  * several Pass-es registered, and execute them in the linear order.
  */
-class PassManager : public OrderedRegistry<Pass> {
+class PassManager : public OrderedRegistry<AnalysisPass> {
  public:
   PassManager() = default;
   // Call all the passes' Initialize methods. The desc and data_flow_graph are
@@ -89,18 +89,6 @@ class DfgPassManager : public PassManager {
   virtual ~DfgPassManager() = default;
 };
 
-/*
- * A pass manager that process a Node each time.
- */
-class NodePassManager : public PassManager {
- public:
-  NodePassManager() = default;
-
-  void RunAll() override;
-
-  virtual ~NodePassManager() = default;
-};
-
 }  // namespace analysis
 }  // namespace inference
 }  // namespace paddle

paddle/fluid/inference/analysis/pass_manager_tester.cc

@@ -34,28 +34,6 @@ class TestDfgPassManager final : public DfgPassManager {
   std::string description() const override { return "test doc"; }
 };
 
-class TestNodePassManager final : public NodePassManager {
- public:
-  virtual ~TestNodePassManager() = default;
-
-  std::string repr() const override { return "test-node-pass-manager"; }
-  std::string description() const override { return "test doc"; }
-};
-
-class TestNodePass final : public NodePass {
- public:
-  virtual ~TestNodePass() = default;
-
-  bool Initialize(Argument* argument) override { return true; }
-
-  void Run(Node* node) override {
-    LOG(INFO) << "- Processing node " << node->repr();
-  }
-
-  std::string repr() const override { return "test-node"; }
-  std::string description() const override { return "some doc"; }
-};
-
 TEST(PassManager, DFG_pass_manager) {
   TestDfgPassManager manager;
   DFG_GraphvizDrawPass::Config config("./", "dfg.dot");
@@ -71,19 +49,6 @@ TEST(PassManager, DFG_pass_manager) {
   manager.RunAll();
 }
 
-TEST(PassManager, Node_pass_manager) {
-  Argument argument(FLAGS_inference_model_dir);
-  // Pre-process: initialize the DFG with the ProgramDesc first.
-  FluidToDataFlowGraphPass pass0;
-  pass0.Initialize(&argument);
-  pass0.Run(argument.main_dfg.get());
-
-  TestNodePassManager manager;
-  manager.Register("test-node-pass", new TestNodePass);
-  ASSERT_TRUE(manager.Initialize(&argument));
-  manager.RunAll();
-}
-
 }  // namespace analysis
 }  // namespace inference
 }  // namespace paddle

paddle/fluid/inference/analysis/tensorrt_subgraph_node_mark_pass.cc

@@ -68,7 +68,7 @@ class DfgDebuggerPass : public DFG_GraphvizDrawPass {
   }
 };
 
-Pass *TensorRTSubgraphNodeMarkPass::CreateGraphvizDebugerPass() const {
+AnalysisPass *TensorRTSubgraphNodeMarkPass::CreateGraphvizDebugerPass() const {
   DFG_GraphvizDrawPass::Config config(FLAGS_IA_graphviz_log_root,
                                       "tensorrt_marked_node");
   return new DfgDebuggerPass(config);

paddle/fluid/inference/analysis/tensorrt_subgraph_node_mark_pass.h

@@ -20,7 +20,7 @@
 #pragma once
 
 #include <string>
-#include "paddle/fluid/inference/analysis/pass.h"
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/subgraph_splitter.h"
 
 namespace paddle {
@@ -48,7 +48,7 @@ class TensorRTSubgraphNodeMarkPass : public DataFlowGraphPass {
     return "tensorrt sub-graph mark pass";
   }
 
-  Pass* CreateGraphvizDebugerPass() const override;
+  AnalysisPass* CreateGraphvizDebugerPass() const override;
   bool Finalize() override;
 
  private:

paddle/fluid/inference/analysis/tensorrt_subgraph_pass.h

@@ -15,8 +15,8 @@ limitations under the License. */
 #pragma once
 
 #include <string>
+#include "paddle/fluid/inference/analysis/analysis_pass.h"
 #include "paddle/fluid/inference/analysis/node.h"
-#include "paddle/fluid/inference/analysis/pass.h"
 #include "paddle/fluid/inference/analysis/subgraph_splitter.h"
 
 namespace paddle {

paddle/fluid/inference/api/CMakeLists.txt

@@ -44,19 +44,7 @@ function(inference_api_test TARGET_NAME)
 endfunction(inference_api_test)
 
 cc_library(paddle_inference_api SRCS api.cc api_impl.cc helper.cc DEPS lod_tensor)
-cc_library(analysis_predictor SRCS analysis_predictor.cc DEPS paddle_inference_api
-          analysis
-          ir_pass_manager
-          pass
-          fc_fuse_pass
-          fc_lstm_fuse_pass
-          seq_concat_fc_fuse_pass
-          graph_viz_pass
-          infer_clean_graph_pass
-          graph_pattern_detector
-          infer_clean_graph_pass
-          attention_lstm_fuse_pass
-  )
+cc_library(analysis_predictor SRCS analysis_predictor.cc DEPS paddle_inference_api analysis)
 
 cc_test(test_paddle_inference_api
         SRCS api_tester.cc

paddle/fluid/operators/fusion_gru_op.cc

@@ -30,14 +30,7 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
                  "Input(WeightX) of GRU should not be null.");
   PADDLE_ENFORCE(ctx->HasInput("WeightH"),
                  "Input(WeightH) of GRU should not be null.");
-
   PADDLE_ENFORCE(ctx->HasOutput("XX"), "Output(XX) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
-                 "Output(ReorderedH0) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                 "Output(BatchedInput) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
-                 "Output(BatchedOut) of GRU should not be null.");
   PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
                  "Output(Hidden) of GRU should not be null.");
 
@@ -80,15 +73,20 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
   }
   framework::DDim out_dims({x_dims[0], frame_size});
   ctx->SetOutputDim("Hidden", out_dims);
-  ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
-  ctx->SetOutputDim("BatchedOut", out_dims);
   ctx->ShareLoD("X", "Hidden");
-
   int xx_width;
   if (ctx->Attrs().Get<bool>("use_seq")) {
     xx_width = wx_dims[1];
   } else {
     xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
+    PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
+                   "Output(ReorderedH0) of GRU should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
+                   "Output(BatchedInput) of GRU should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
+                   "Output(BatchedOut) of GRU should not be null.");
+    ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
+    ctx->SetOutputDim("BatchedOut", out_dims);
   }
   ctx->SetOutputDim("XX", {x_dims[0], xx_width});
   ctx->ShareLoD("X", "XX");

paddle/fluid/platform/dynload/dynamic_loader.cc

@@ -121,6 +121,12 @@ static inline void* GetDsoHandleFromSearchPath(const std::string& search_root,
     if (nullptr == dso_handle) {
       LOG(WARNING) << "Failed to find dynamic library: " << dlPath << " ("
                    << dlerror() << ")";
+      if (dlPath.find("nccl") != std::string::npos) {
+        std::cout
+            << "You may need to install 'nccl2' from NVIDIA official website: "
+            << "https://developer.nvidia.com/nccl/nccl-download"
+            << "before install PaddlePaddle" << std::endl;
+      }
       dlPath = dso_name;
       dso_handle = GetDsoHandleFromDefaultPath(dlPath, dynload_flags);
     }

paddle/scripts/paddle_build.sh

@@ -500,7 +500,7 @@ EOF
 EOF
 
     if [[ ${WITH_GPU} == "ON"  ]]; then
-        NCCL_DEPS="apt-get install -y --allow-downgrades libnccl2=2.1.2-1+cuda${CUDA_MAJOR} libnccl-dev=2.1.2-1+cuda${CUDA_MAJOR} &&"
+        NCCL_DEPS="apt-get install -y --allow-downgrades libnccl2=2.2.13-1+cuda${CUDA_MAJOR} libnccl-dev=2.2.13-1+cuda${CUDA_MAJOR} &&"
     else
         NCCL_DEPS=""
     fi

python/paddle/dataset/image.py

@@ -104,7 +104,7 @@ def batch_images_from_tar(data_file,
                 pickle.dump(
                     output,
                     open('%s/batch_%d' % (out_path, file_id), 'wb'),
-                    protocol=pickle.HIGHEST_PROTOCOL)
+                    protocol=2)
                 file_id += 1
                 data = []
                 labels = []
@@ -113,9 +113,7 @@ def batch_images_from_tar(data_file,
         output['label'] = labels
         output['data'] = data
         pickle.dump(
-            output,
-            open('%s/batch_%d' % (out_path, file_id), 'wb'),
-            protocol=pickle.HIGHEST_PROTOCOL)
+            output, open('%s/batch_%d' % (out_path, file_id), 'wb'), protocol=2)
 
     with open(meta_file, 'a') as meta:
         for file in os.listdir(out_path):

python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py

@@ -47,14 +47,14 @@ def train_program():
     loss = fluid.layers.square_error_cost(input=y_predict, label=y)
     avg_loss = fluid.layers.mean(loss)
 
-    return avg_loss
+    return [avg_loss, y_predict]
 
 
 def optimizer_func():
     return fluid.optimizer.SGD(learning_rate=0.001)
 
 
-def train(use_cuda, train_program, params_dirname):
+def train(use_cuda, train_program, params_dirname, inference_model_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     trainer = fluid.Trainer(
@@ -74,6 +74,8 @@ def train(use_cuda, train_program, params_dirname):
                 '''
                 if params_dirname is not None:
                     trainer.save_params(params_dirname)
+                    trainer.save_inference_model(inference_model_dirname,
+                                                 ['x'], [1])
                 trainer.stop()
 
     trainer.train(
@@ -99,15 +101,55 @@ def infer(use_cuda, inference_program, params_dirname=None):
     print("infer results: ", results[0])
 
 
+def infer_by_saved_model(use_cuda, save_dirname=None):
+    if save_dirname is None:
+        return
+
+    place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+    exe = fluid.Executor(place)
+
+    inference_scope = fluid.core.Scope()
+    with fluid.scope_guard(inference_scope):
+        # Use fluid.io.load_inference_model to obtain the inference program desc,
+        # the feed_target_names (the names of variables that will be feeded
+        # data using feed operators), and the fetch_targets (variables that
+        # we want to obtain data from using fetch operators).
+        [inference_program, feed_target_names,
+         fetch_targets] = fluid.io.load_inference_model(save_dirname, exe)
+
+        # The input's dimension should be 2-D and the second dim is 13
+        # The input data should be >= 0
+        batch_size = 10
+
+        test_reader = paddle.batch(
+            paddle.dataset.uci_housing.test(), batch_size=batch_size)
+
+        test_data = next(test_reader())
+        test_feat = numpy.array(
+            [data[0] for data in test_data]).astype("float32")
+        test_label = numpy.array(
+            [data[1] for data in test_data]).astype("float32")
+
+        assert feed_target_names[0] == 'x'
+        results = exe.run(inference_program,
+                          feed={feed_target_names[0]: numpy.array(test_feat)},
+                          fetch_list=fetch_targets)
+        print("infer shape: ", results[0].shape)
+        print("infer results: ", results[0])
+        print("ground truth: ", test_label)
+
+
 def main(use_cuda):
     if use_cuda and not fluid.core.is_compiled_with_cuda():
         return
 
     # Directory for saving the trained model
-    params_dirname = "fit_a_line.inference.model"
+    params_dirname = "fit_a_line.model"
+    inference_model_dirname = "fit_a_line.inference_model"
 
-    train(use_cuda, train_program, params_dirname)
+    train(use_cuda, train_program, params_dirname, inference_model_dirname)
     infer(use_cuda, inference_program, params_dirname)
+    infer_by_saved_model(use_cuda, inference_model_dirname)
 
 
 class TestFitALine(unittest.TestCase):

python/paddle/fluid/tests/unittests/test_dist_base.py

@@ -55,6 +55,7 @@ class TestDistRunnerBase(object):
         pserver_prog = t.get_pserver_program(args.current_endpoint)
         startup_prog = t.get_startup_program(args.current_endpoint,
                                              pserver_prog)
+
         place = fluid.CPUPlace()
         exe = fluid.Executor(place)
         exe.run(startup_prog)
@@ -147,6 +148,8 @@ def runtime_main(test_class):
 
 
 import paddle.compat as cpt
+import socket
+from contextlib import closing
 
 
 class TestDistBase(unittest.TestCase):
@@ -156,13 +159,19 @@ class TestDistBase(unittest.TestCase):
     def setUp(self):
         self._trainers = 2
         self._pservers = 2
-        self._ps_endpoints = "127.0.0.1:9123,127.0.0.1:9124"
+        self._ps_endpoints = "127.0.0.1:%s,127.0.0.1:%s" % (
+            self._find_free_port(), self._find_free_port())
         self._python_interp = "python"
         self._sync_mode = True
         self._mem_opt = False
         self._use_reduce = False
         self._setup_config()
 
+    def _find_free_port(self):
+        with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
+            s.bind(('', 0))
+            return s.getsockname()[1]
+
     def start_pserver(self, model_file, check_error_log):
         ps0_ep, ps1_ep = self._ps_endpoints.split(",")
         ps_cmd = "%s %s --role pserver --endpoints %s --trainer_id 0 --current_endpoint %s --trainers %d --is_dist"

python/paddle/fluid/tests/unittests/test_fusion_lstm_op.py

@@ -53,12 +53,11 @@ class TestFusionLSTMOp(OpTest):
         self.M = 8
         self.D = 16
         self.has_initial_state = False
+        self.use_peepholes = False
         self.is_reverse = False
         self.act_gate = 'sigmoid'
         self.act_cell = 'tanh'
         self.act_cand = 'tanh'
-        self.use_peepholes = False
-        self.use_seq = False
         self.set_conf()
 
         T = sum(self.lod[0])
@@ -108,7 +107,6 @@ class TestFusionLSTMOp(OpTest):
         }
         self.attrs = {
             'use_peepholes': self.use_peepholes,
-            'use_seq': self.use_seq,
             'is_reverse': self.is_reverse,
             'gate_activation': self.act_gate,
             'cell_activation': self.act_cell,
@@ -178,50 +176,18 @@ class TestFusionLSTMOpPeepholesReverse(TestFusionLSTMOp):
         self.is_reverse = True
 
 
-class TestFusionLSTMOpPoopholesBS1(TestFusionLSTMOp):
+class TestFusionLSTMOpPeepholesInitReverse(TestFusionLSTMOp):
     def set_conf(self):
         self.use_peepholes = True
-        self.lod = [[3]]
-        self.D = 16
-
-
-class TestFusionLSTMOpSeqInit(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.has_initial_state = True
-
-
-class TestFusionLSTMOpSeqReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.is_reverse = True
-
-
-class TestFusionLSTMOpSeqInitReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
         self.has_initial_state = True
         self.is_reverse = True
 
 
-class TestFusionLSTMOpSeqPeepholes(TestFusionLSTMOp):
+class TestFusionLSTMOpPeepholesBS1(TestFusionLSTMOp):
     def set_conf(self):
-        self.use_seq = True
         self.use_peepholes = True
-
-
-class TestFusionLSTMOpSeqPeepholesInit(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.use_peepholes = True
-        self.has_initial_state = True
-
-
-class TestFusionLSTMOpSeqPeepholesReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.use_peepholes = True
-        self.is_reverse = True
+        self.lod = [[2]]
+        self.D = 8
 
 
 if __name__ == '__main__':

python/paddle/fluid/tests/unittests/test_parallel_executor_fetch_feed.py

@@ -85,6 +85,7 @@ class TestFetchOp(unittest.TestCase):
                     assert not math.isnan(np.sum(ret[i])) and \
                            not math.isinf(np.sum(ret[i]))
 
+    @unittest.skip(reason="CI timeout")
     def test_fetch_op(self):
         tst_reader = paddle.batch(flowers.test(use_xmap=False), batch_size=16)
         tst_reader_iter = tst_reader()
@@ -139,6 +140,7 @@ class TestFeedParallel(unittest.TestCase):
             if batch_id == 2:
                 break
 
+    @unittest.skip(reason="CI timeout")
     def test_feed_op(self):
         os.environ['CPU_NUM'] = str(4)
         if core.is_compiled_with_cuda():

python/paddle/fluid/trainer.py

@@ -431,6 +431,28 @@ class Trainer(object):
             exe = executor.Executor(self.place)
             io.save_persistables(exe, dirname=param_path)
 
+    def save_inference_model(self, param_path, feeded_var_names,
+                             target_var_indexes):
+        """
+        Save model for cpp inference into :code:`param_path`.
+
+        Args:
+            param_path(str): The path to save parameters.
+            feeded_var_names(list(str)): The name of the vars that you
+                need to feed in before run program.
+            target_var_indexes(list(int)): the index of target var that
+                you need to return in trainer.train_func.
+        Returns:
+            None
+        """
+        with self._prog_and_scope_guard():
+            exe = executor.Executor(self.place)
+            target_vars = [
+                self.train_func_outputs[index] for index in target_var_indexes
+            ]
+            io.save_inference_model(param_path, feeded_var_names, target_vars,
+                                    exe)
+
     @contextlib.contextmanager
     def _prog_and_scope_guard(self):
         with framework.program_guard(