1. delete unused file

2. refine after mrege from github

paddle/fluid/lite/api/CMakeLists.txt

@@ -43,8 +43,6 @@ endif()
 #     lite_cc_test(test_light_api SRCS light_api_test.cc DEPS light_api_lite ARGS --optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt SERIAL)
 # endif()
 
-message(STATUS "!!!"  ${ops_lite})
-message(STATUS "!!!" ${arm_kernels})
 lite_cc_binary(cxx_api_lite_bin SRCS cxx_api_bin.cc
     DEPS
     cxx_api_lite

paddle/fluid/lite/core/mir/fusion/CMakeLists.txt

@@ -14,5 +14,9 @@ set(mir_fusers
     fuse_conv_bn
     CACHE INTERNAL "fusers")
 
+if (LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
+    return()
+endif()
+
 lite_cc_test(test_lite_conv_bn_fuse SRCS conv_bn_fuse_pass_test.cc
    DEPS elementwise_ops_lite batch_norm_op_lite conv_op_lite proto_desc compatible_pb_lite program_lite mir_pass mir_pass_manager pattern_matcher_high_api)

paddle/fluid/lite/core/mir/fusion/conv_bn_fuser.cc

@@ -84,9 +84,9 @@ void ConvBNFuser::InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) {
                         ->GetMutable<lite::Tensor>();
   size_t bias_size = bn_scale_t->data_size();
   auto bn_scale_d = bn_scale_t->mutable_data<float>();
-  PADDLE_ENFORCE(bias_size == conv_weight_dims[0],
-                 "The BN bias's size should be equal to the size of the first "
-                 "dim size of the conv weights");
+  CHECK(bias_size == conv_weight_dims[0])
+      << "The BN bias's size should be equal to the size of the first "
+      << "dim size of the conv weights";
 
   auto bn_mean_t = scope->FindVar(matched.at("bn_mean")->arg()->name)
                        ->GetMutable<lite::Tensor>();

paddle/fluid/lite/core/mir/pattern_matcher.cc

@@ -409,8 +409,8 @@ PMNode *PMNode::assert_is_op_output(const std::string &op_type) {
 
 bool IsNthOutput(const Node *var, const Node *op, const std::string &argument,
                  size_t nth) {
-  PADDLE_ENFORCE(var->IsArg());
-  PADDLE_ENFORCE(op->IsStmt());
+  CHECK(var->IsArg());
+  CHECK(op->IsStmt());
   auto op_info = op->stmt()->op_info();
   if (op_info->Output(argument).size() <= nth) return false;
   return var->arg()->name == op_info->Output(argument)[nth];
@@ -418,8 +418,8 @@ bool IsNthOutput(const Node *var, const Node *op, const std::string &argument,
 
 bool IsNthInput(const Node *var, const Node *op, const std::string &argument,
                 size_t nth) {
-  PADDLE_ENFORCE(var->IsArg());
-  PADDLE_ENFORCE(op->IsStmt());
+  CHECK(var->IsArg());
+  CHECK(op->IsStmt());
   auto op_info = op->stmt()->op_info();
   if (op_info->Input(argument).size() <= nth) return false;
   return var->arg()->name == op_info->Input(argument)[nth];

paddle/fluid/lite/core/mir/ssa_graph.cc

@@ -26,8 +26,6 @@ namespace mir {
 bool SSAGraph::CheckBidirectionalConnection() {
   LOG(INFO) << "node count " << node_storage_.size();
   for (auto &node : node_storage_) {
-    if (node.IsStmt()) LOG(INFO) << node.AsStmt().op_info()->Type();
-    if (node.IsArg()) LOG(INFO) << node.AsArg().name << " " << node.AsArg().id;
     for (auto *in : node.inlinks) {
       CHECK(in->outlinks.end() !=
             std::find(in->outlinks.begin(), in->outlinks.end(), &node));
@@ -123,11 +121,8 @@ void SSAGraph::Build(const Program &program,
 
   std::unordered_map<std::string, mir::Node *> arg_update_node_map_;
   for (auto &op : program.ops()) {
-    LOG(INFO) << op->op_info()->Type();
     auto *op_node = GraphCreateInstructNode(op, valid_places);
-    LOG(INFO) << "input:";
     for (const std::string &name : op->op_info()->input_names()) {
-      LOG(INFO) << name;
       mir::Node *arg_node = nullptr;
       if (arg_update_node_map_.count(name)) {
         arg_node = arg_update_node_map_.at(name);
@@ -141,9 +136,7 @@ void SSAGraph::Build(const Program &program,
       CHECK(arg_node->IsRoleSet());
       DirectedLink(arg_node, op_node);
     }
-    LOG(INFO) << "output:";
     for (const std::string &name : op->op_info()->output_names()) {
-      LOG(INFO) << name;
       node_storage_.emplace_back();
       auto *arg_node = &node_storage_.back();
       arg_node->AsArg(name, node_storage_.size() - 1);

paddle/fluid/lite/core/optimizer.h

@@ -46,27 +46,33 @@ class Optimizer {
     SpecifyKernelPickTactic(kernel_pick_factor);
     InitTargetTypeTransformPass();
 
-#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
+    // #ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
     if (passes.empty()) {
       RunPasses(std::vector<std::string>{{
+          "graph_visualze",                           //
           "lite_conv_bn_fuse_pass",                   //
+          "graph_visualze",                           //
           "lite_conv_elementwise_add_act_fuse_pass",  //
+          "graph_visualze",                           //
           "lite_fc_fuse_pass",                        //
           "static_kernel_pick_pass",                  //
-          "variable_place_inference_pass",            //
-          "argument_type_display_pass",               //
-          "type_target_transform_pass",               //
-          "argument_type_display_pass",               //
-          "variable_place_inference_pass",            //
-          "argument_type_display_pass",               //
-          "io_copy_kernel_pick_pass",                 //
-          "variable_place_inference_pass",            //
+                                                      /*
+                                                        "variable_place_inference_pass",            //
+                                                        "argument_type_display_pass",               //
+                                                        "type_target_transform_pass",               //
+                                                       // "argument_type_display_pass",               //
+                                                        "variable_place_inference_pass",            //
+                                                        "argument_type_display_pass",               //
+                                                        "io_copy_kernel_pick_pass",                 //
+                                                        "variable_place_inference_pass",            //
+                                                        "graph_visualze", //
+                                                      */
           "runtime_context_assign_pass",              //
       }});
     } else {
       RunPasses(passes);
     }
-#endif
+    // #endif
     exec_scope_ = program.exec_scope();
   }
 

paddle/fluid/lite/operators/batch_norm.cc

-// Copyright (c) 2019 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/lite/operators/batch_norm.h"
-#include <vector>
-#include "paddle/fluid/lite/core/op_registry.h"
-
-namespace paddle {
-namespace lite {
-namespace operators {
-
-bool BatchNormOpLite::CheckShape() const { return true; }
-
-bool BatchNormOpLite::InferShape() const { return true; }
-
-}  // namespace operators
-}  // namespace lite
-}  // namespace paddle
-
-REGISTER_LITE_OP(batch_norm, paddle::lite::operators::BatchNormOpLite);

paddle/fluid/lite/operators/batch_norm.h

-// Copyright (c) 2019 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 <string>
-#include <vector>
-#include "paddle/fluid/lite/core/kernel.h"
-#include "paddle/fluid/lite/core/op_lite.h"
-#include "paddle/fluid/lite/core/scope.h"
-#include "paddle/fluid/lite/operators/op_params.h"
-#include "paddle/fluid/lite/utils/all.h"
-
-namespace paddle {
-namespace lite {
-namespace operators {
-
-class BatchNormOpLite : public OpLite {
- public:
-  BatchNormOpLite() {}
-
-  explicit BatchNormOpLite(const std::string &type) : OpLite(type) {}
-
-  bool CheckShape() const override;
-
-  bool InferShape() const override;
-
-  void AttachKernel(KernelBase *kernel) override { kernel->SetParam(param_); }
-  // TODO(Superjomn) replace framework::OpDesc with a lite one.
-  bool AttachImpl(const cpp::OpDesc &op_desc, lite::Scope *scope) override {
-    auto x = op_desc.Input("X").front();
-    auto bias = op_desc.Input("Bias").front();
-    auto mean = op_desc.Input("Mean").front();
-    auto scale = op_desc.Input("Scale").front();
-    auto variance = op_desc.Input("Variance").front();
-
-    auto out = op_desc.Output("Y").front();
-    auto mean_out = op_desc.Output("MeanOut").front();
-    auto var_out = op_desc.Output("VarianceOut").front();
-    auto saved_mean = op_desc.Output("SavedMean").front();
-    auto saved_var = op_desc.Output("SavedVariance").front();
-
-    auto *var = scope->FindVar(x);
-    param_.x = var->GetMutable<Tensor>();
-    var = scope->FindVar(bias);
-    param_.bias = var->GetMutable<Tensor>();
-    var = scope->FindVar(mean);
-    param_.mean = var->GetMutable<Tensor>();
-    var = scope->FindVar(scale);
-    param_.scale = var->GetMutable<Tensor>();
-    var = scope->FindVar(variance);
-    param_.var = var->GetMutable<Tensor>();
-    var = scope->FindVar(out);
-    param_.out = var->GetMutable<Tensor>();
-    var = scope->FindVar(mean_out);
-    param_.mean_out = var->GetMutable<Tensor>();
-    var = scope->FindVar(var_out);
-    param_.var_out = var->GetMutable<Tensor>();
-    var = scope->FindVar(saved_mean);
-    param_.saved_mean = var->GetMutable<Tensor>();
-    var = scope->FindVar(saved_var);
-    param_.saved_var = var->GetMutable<Tensor>();
-
-    param_.eps = op_desc.GetAttr<float>("epsilon");
-
-    return true;
-  }
-
-  std::string DebugString() const override { return "batch_norm"; }
-
- private:
-  mutable BatchNormParam param_;
-};
-
-}  // namespace operators
-}  // namespace lite
-}  // namespace paddle

paddle/fluid/lite/operators/batch_norm_op.cc

@@ -82,7 +82,7 @@ bool BatchNormOp::AttachImpl(const cpp::OpDesc &op_desc, lite::Scope *scope) {
   param_.variance =
       scope->FindVar(op_desc.Input("Variance").front())->GetMutable<Tensor>();
   param_.y = scope->FindVar(op_desc.Output("Y").front())->GetMutable<Tensor>();
-  param_.is_test = op_desc.GetAttr<bool>("is_test");
+  param_.is_test = op_desc.GetAttr<int>("is_test");
   param_.use_global_stats = op_desc.GetAttr<bool>("use_global_stats");
   if (!param_.is_test) {
     param_.mean_out =