Merge pull request #360 from cocodark/develop

remove unused code

src/framework/attribute.cpp

@@ -17,14 +17,8 @@ limitations under the License. */
 namespace paddle_mobile {
 namespace framework {
 
-/*
- * Variant<int, float, std::string, std::vector<int>, std::vector<float>,
-          std::vector<std::string>, bool, std::vector<bool>, BlockDesc *,
-          int64_t>
- * */
-
 struct PrintVistor : Vistor<Print &> {
-  PrintVistor(Print &printer) : printer_(printer) {}
+  explicit PrintVistor(Print &printer) : printer_(printer) {}
   template <typename T>
   Print &operator()(const T &value) {
     printer_ << value;

src/framework/attribute.h

@@ -14,7 +14,9 @@ limitations under the License. */
 
 #pragma once
 
+#include <string>
 #include <unordered_map>
+#include <vector>
 #include "common/enforce.h"
 #include "common/log.h"
 #include "common/variant.h"
@@ -22,28 +24,15 @@ limitations under the License. */
 
 namespace paddle_mobile {
 namespace framework {
+using std::string;
+using std::vector;
 
 class BlockDesc;
 
 class Attribute {
  public:
-  /*
-   *  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__INT = 0,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__FLOAT = 1,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__STRING = 2,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__INTS = 3,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__FLOATS = 4,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__STRINGS = 5,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BOOLEAN = 6,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BOOLEANS = 7,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BLOCK = 8,
-  PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__LONG = 9
-    PROTOBUF_C__FORCE_ENUM_TO_BE_INT_SIZE(PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE)
-   *
-   * */
   static Attribute GetAttrValue(
       PaddleMobile__Framework__Proto__OpDesc__Attr *attr_desc) {
-    //    std::cout << "begin get attr value" << std::endl;
     Attribute attr;
     switch (attr_desc->type) {
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BOOLEAN: {
@@ -63,35 +52,35 @@ class Attribute {
         break;
       }
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BOOLEANS: {
-        std::vector<bool> val(attr_desc->n_bools);
+        vector<bool> val(attr_desc->n_bools);
         for (int i = 0; i < attr_desc->n_bools; ++i) {
           val[i] = attr_desc->bools[i];
         }
-        attr.Set<std::vector<bool>>(val);
+        attr.Set<vector<bool>>(val);
         break;
       }
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__INTS: {
-        std::vector<int> val(attr_desc->n_ints);
+        vector<int> val(attr_desc->n_ints);
         for (int i = 0; i < attr_desc->n_ints; ++i) {
           val[i] = attr_desc->ints[i];
         }
-        attr.Set<std::vector<int>>(val);
+        attr.Set<vector<int>>(val);
         break;
       }
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__FLOATS: {
-        std::vector<float> val(attr_desc->n_floats);
+        vector<float> val(attr_desc->n_floats);
         for (int i = 0; i < attr_desc->n_floats; ++i) {
           val[i] = attr_desc->floats[i];
         }
-        attr.Set<std::vector<float>>(val);
+        attr.Set<vector<float>>(val);
         break;
       }
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__STRINGS: {
-        std::vector<std::string> val(attr_desc->n_strings);
+        vector<string> val(attr_desc->n_strings);
         for (int i = 0; i < attr_desc->n_strings; ++i) {
           val[i] = attr_desc->strings[i];
         }
-        attr.Set<std::vector<std::string>>(val);
+        attr.Set<vector<string>>(val);
         break;
       }
       case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__LONG: {
@@ -122,21 +111,18 @@ class Attribute {
       return vistor(attr.variant_.Get<int>());
     } else if (attr.variant_.TypeId() == typeid(float).hash_code()) {
       return vistor(attr.variant_.Get<float>());
-    } else if (attr.variant_.TypeId() == typeid(std::string).hash_code()) {
-      return vistor(attr.variant_.Get<std::string>());
-    } else if (attr.variant_.TypeId() == typeid(std::vector<int>).hash_code()) {
-      return vistor(attr.variant_.Get<std::vector<int>>());
-    } else if (attr.variant_.TypeId() ==
-               typeid(std::vector<float>).hash_code()) {
-      return vistor(attr.variant_.Get<std::vector<float>>());
-    } else if (attr.variant_.TypeId() ==
-               typeid(std::vector<std::string>).hash_code()) {
-      return vistor(attr.variant_.Get<std::vector<std::string>>());
+    } else if (attr.variant_.TypeId() == typeid(string).hash_code()) {
+      return vistor(attr.variant_.Get<string>());
+    } else if (attr.variant_.TypeId() == typeid(vector<int>).hash_code()) {
+      return vistor(attr.variant_.Get<vector<int>>());
+    } else if (attr.variant_.TypeId() == typeid(vector<float>).hash_code()) {
+      return vistor(attr.variant_.Get<vector<float>>());
+    } else if (attr.variant_.TypeId() == typeid(vector<string>).hash_code()) {
+      return vistor(attr.variant_.Get<vector<string>>());
     } else if (attr.variant_.TypeId() == typeid(bool).hash_code()) {
       return vistor(attr.variant_.Get<bool>());
-    } else if (attr.variant_.TypeId() ==
-               typeid(std::vector<bool>).hash_code()) {
-      return vistor(attr.variant_.Get<std::vector<bool>>());
+    } else if (attr.variant_.TypeId() == typeid(vector<bool>).hash_code()) {
+      return vistor(attr.variant_.Get<vector<bool>>());
     } else if (attr.variant_.TypeId() == typeid(int64_t).hash_code()) {
       return vistor(attr.variant_.Get<int64_t>());
     } else {
@@ -145,24 +131,21 @@ class Attribute {
   }
 
  private:
-  Variant<int, float, std::string, std::vector<int>, std::vector<float>,
-          std::vector<std::string>, bool, std::vector<bool>, BlockDesc *,
-          int64_t>
+  Variant<int, float, string, vector<int>, vector<float>, vector<string>, bool,
+          vector<bool>, BlockDesc *, int64_t>
       variant_;
 };
 
-using AttributeMap = std::unordered_map<std::string, Attribute>;
+using AttributeMap = std::unordered_map<string, Attribute>;
 
 class AttrReader {
  public:
   explicit AttrReader(const AttributeMap &attrs) : attrs_(attrs) {}
 
   template <typename T>
-  inline T Get(const std::string &name) const {
-    //          PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should
-    //          be in
-    //          AttributeMap",
-    //                         name);
+  inline T Get(const string &name) const {
+    PADDLE_MOBILE_ENFORCE(attrs_.count(name) != 0,
+                          "%s should  be in AttributeMap", name);
     return ((Attribute)attrs_.at(name)).Get<T>();
   }
 

src/framework/data_layout.h

@@ -54,7 +54,6 @@ inline std::string DataLayoutToString(const DataLayout &data_layout) {
       return "ANY_LAYOUT";
     default:
       break;
-      //      std::cout << "unknown DataLayou %d", data_layout;
   }
 }
 

src/framework/data_transform.cpp

-/* Copyright (c) 2018 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 "framework/data_transform.h"
-
-namespace paddle_mobile {
-namespace framework {
-
-static void PassTensorData(Tensor *from, Tensor *to) {
-  to->ShareDataWith(*from);
-  *from = Tensor();
-}
-
-void DataTransform(const OpKernelType &expected_kernel_type,
-                   const OpKernelType &kernel_type_for_var,
-                   const Tensor &input_tensor, Tensor *output_tensor) {
-  bool transformed = false;
-  Tensor in;
-  in.ShareDataWith(input_tensor);
-  Tensor out;
-
-  //  // do layout transform
-  //  if (NeedTransformLayout(expected_kernel_type.data_layout_,
-  //                          kernel_type_for_var.data_layout_)) {
-  //    TransDataLayout(kernel_type_for_var, expected_kernel_type, in,
-  //    &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  // do data type transform
-  //  if (expected_kernel_type.data_type_ !=
-  //  kernel_type_for_var.data_type_) {
-  //    TransDataType(kernel_type_for_var, expected_kernel_type, in,
-  //    &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  // do device transform
-  //  if (!platform::is_same_place(kernel_type_for_var.place_,
-  //                               expected_kernel_type.place_)) {
-  //    TransDataDevice(in, expected_kernel_type.place_, &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  PADDLE_ENFORCE(transformed, "No transform is applied, please
-  //  check!");
-  // get output data
-  output_tensor->ShareDataWith(in);
-}
-
-void CopyVariableWithTensor(const Variable &in_var, const Tensor &tensor,
-                            Variable *out_var) {
-  //  if (in_var.IsType<LoDTensor>()) {
-  //    auto& in_lod_tensor = in_var.Get<LoDTensor>();
-  //    auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
-  //    tran_lod_tensor->set_lod(in_lod_tensor.lod());
-  //    tran_lod_tensor->set_layout(in_lod_tensor.layout());
-  //    tran_lod_tensor->ShareDataWith(tensor);
-  //  } else if (in_var.IsType<SelectedRows>()) {
-  //    auto& in_selected_rows = in_var.Get<SelectedRows>();
-  //    auto* trans_selected_rows =
-  //    out_var.GetMutable<SelectedRows>();
-  //    trans_selected_rows->set_height(in_selected_rows.height());
-  //    trans_selected_rows->set_rows(in_selected_rows.rows());
-  //    trans_selected_rows->mutable_value()->ShareDataWith(tensor);
-  //  } else {
-  //    PADDLE_THROW("unknown var type");
-  //  }
-}
-
-}  // namespace framework
-}  // namespace paddle_mobile

src/framework/data_type.h

-/* Copyright (c) 2018 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
-
-namespace paddle_mobile {
-namespace framework {
-
-//    inline proto::VarType::Type ToDataType(std::type_index type) {
-//        using namespace paddle_mobile::framework::proto;
-//        if (typeid(float).hash_code() == type.hash_code()) {
-//            return proto::VarType::FP32;
-//        } else if (typeid(double).hash_code() == type.hash_code()) {
-//            return proto::VarType::FP64;
-//        } else if (typeid(int).hash_code() == type.hash_code()) {
-//            return proto::VarType::INT32;
-//        } else if (typeid(int64_t).hash_code() == type.hash_code()) {
-//            return proto::VarType::INT64;
-//        } else if (typeid(bool).hash_code() == type.hash_code()) {
-//            return proto::VarType::BOOL;
-//        } else {
-////            PADDLE_THROW("Not supported");
-//        }
-//    }
-}  // namespace framework
-}  // namespace paddle_mobile

src/framework/ddim.cpp

@@ -183,7 +183,7 @@ DDim DDim::operator*(DDim d) const {
 
 int64_t get(const DDim &ddim, int idx) { return ddim[idx]; }
 
-void set(DDim &ddim, int idx, int value) { ddim[idx] = value; }
+void set(DDim *ddim, int idx, int value) { (*ddim)[idx] = value; }
 
 /// @cond HIDDEN
 struct VectorizeVisitor : Vistor<void> {

src/framework/ddim.h

@@ -83,17 +83,6 @@ struct DDim {
 
   int64_t operator[](int idx) const;
 
-  //  template <typename Visitor>
-  //  typename Visitor::result_type apply_visitor(Visitor& visitor) {
-  //    return var.apply_visitor(visitor);
-  //  }
-  //
-  //  template <typename Visitor>
-  //  typename Visitor::result_type apply_visitor(Visitor& visitor)
-  //  const {
-  //    return var.apply_visitor(visitor);
-  //  }
-
   DDimVar getVar() { return var; }
 
   bool operator==(DDim d) const;
@@ -126,7 +115,7 @@ DDim make_ddim(std::initializer_list<int64_t> dims);
 
 int64_t get(const DDim &dim, int idx);
 
-void set(DDim &dim, int idx, int val);
+void set(DDim *dim, int idx, int val);
 
 std::vector<int64_t> vectorize(const DDim &ddim);
 

src/framework/lod_tensor.cpp

@@ -42,23 +42,10 @@ std::ostream &operator<<(std::ostream &os, const LoD &lod) {
 }
 
 std::ostream &operator<<(std::ostream &os, const LoDTensor &t) {
-  //  PADDLE_ENFORCE(t.type().hash_code() ==
-  //  typeid(float).hash_code());
-
-  //  if (!platform::is_cpu_place(t.place())) {
-  //    LoDTensor tt;
-  //    framework::TensorCopy(t, platform::CPUPlace(), &tt);
-  //    platform::DeviceContextPool &pool =
-  //    platform::DeviceContextPool::Instance(); auto &dev_ctx =
-  //    *pool.Get(t.place()); dev_ctx.Wait();
-  //
-  //    os << tt;
-  //    return os;
-  //  }
-
+  PADDLE_MOBILE_ENFORCE(t.type().hash_code() == typeid(float).hash_code(),
+                        "t.type() is not float");
   os << "dim: " << t.dims() << "\n";
   os << "lod: " << t.lod() << "\n";
-
   // only print first ten elements
   int64_t size = t.numel() < 10 ? t.numel() : 10;
   for (int64_t i = 0; i < size; ++i) {
@@ -76,9 +63,9 @@ std::string LoDToString(const LoD &lod) {
 
 LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
                  size_t elem_end) {
-  //  PADDLE_ENFORCE_LT(level, in.size());
-  //  PADDLE_ENFORCE_LT(elem_end, in[level].size());
-
+  PADDLE_MOBILE_ENFORCE(level < in.size(), "level should >= in.size()");
+  PADDLE_MOBILE_ENFORCE(elem_end < in[level].size(),
+                        "elem_end >= in[level].size()");
   LoD res;
   res.resize(in.size() - level);
   // copy the first level
@@ -211,8 +198,9 @@ LoDAndOffset GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx,
   LoD sub_lod;
 
   for (size_t level_idx = start_level; level_idx < lod.size(); ++level_idx) {
-    //    PADDLE_ENFORCE_LE(start_idx, end_idx);
-    //    PADDLE_ENFORCE_LT(end_idx, lod[level_idx].size());
+    PADDLE_MOBILE_ENFORCE(start_idx <= end_idx, "start_idx > end_idx");
+    PADDLE_MOBILE_ENFORCE(end_idx < lod[level_idx].size(),
+                          "end_idx >= lod[level_idx].size()");
     std::vector<size_t> level_lens;
     for (size_t i = start_idx; i < end_idx; ++i) {
       level_lens.push_back(lod[level_idx][i + 1] - lod[level_idx][i]);
@@ -226,10 +214,9 @@ LoDAndOffset GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx,
 }
 
 void AppendLoD(LoD *lod, const LoD &lod_length) {
-  //  PADDLE_ENFORCE(
-  //      lod->empty() || lod->size() == lod_length.size(),
-  //      "The lod_length should has the same size with the appended
-  //      lod.");
+  PADDLE_MOBILE_ENFORCE(
+      lod->empty() || lod->size() == lod_length.size(),
+      "The lod_length should has the same size with the appended lod.");
   if (lod->empty()) {
     for (size_t i = 0; i < lod_length.size(); ++i) {
       lod->emplace_back(1, 0);  // size = 1, value = 0;

src/framework/op_info.h

@@ -25,9 +25,8 @@ template <typename Dtype>
 struct OpInfo {
   OpCreator<Dtype> creator_;
   const OpCreator<Dtype> &Creator() const {
-    //    PADDLE_ENFORCE_NOT_NULL(creator_,
-    //                            "Operator Creator has not been
-    //                            registered");
+    PADDLE_MOBILE_ENFORCE(creator_ != nullptr,
+                          "Operator Creator has not been registered");
     return creator_;
   }
 };
@@ -48,17 +47,15 @@ class OpInfoMap {
   }
 
   void Insert(const std::string &type, const OpInfo<Dtype> &info) {
-    //    PADDLE_ENFORCE(!Has(type), "Operator %s has been
-    //    registered", type);
+    PADDLE_MOBILE_ENFORCE(!Has(type), "Operator %s has been registered",
+                          type.c_str());
     map_.insert({type, info});
   }
 
   const OpInfo<Dtype> &Get(const std::string &type) const {
     auto op_info_ptr = GetNullable(type);
-    //    PADDLE_ENFORCE_NOT_NULL(op_info_ptr, "Operator %s has not
-    //    been
-    //    registered",
-    //                            type);
+    PADDLE_MOBILE_ENFORCE(op_info_ptr != nullptr,
+                          "Operator %s has not been registered", type.c_str());
     return *op_info_ptr;
   }
 

src/framework/scope.cpp

@@ -76,7 +76,6 @@ void Scope::DeleteScope(Scope *scope) const {
   auto it = std::find(kids_.begin(), kids_.end(), scope);
   kids_.erase(it);
   delete scope;
-  // deferent
 }
 
 void Scope::EraseVars(const std::vector<std::string> &var_names) {
@@ -104,14 +103,6 @@ void Scope::Rename(const std::string &origin_name,
   vars_[new_name] = origin_it->second;
   vars_.erase(origin_it);
 }
-//
-//            std::string Scope::Rename(const std::string& origin_name)
-//            const {
-//                auto var_name = string::Sprintf("%p.%d", this,
-//                vars_.size());
-//                Rename(origin_name, var_name);
-//                return var_name;
-//            }
 
 Variable *Scope::FindVarLocally(const std::string &name) const {
   auto it = vars_.find(name);

src/operators/conv_op.cpp

@@ -14,7 +14,6 @@ limitations under the License. */
 
 #include "operators/conv_op.h"
 #include <vector>
-#include "framework/data_type.h"
 #include "framework/op_proto_maker.h"
 #include "framework/op_registry.h"
 

src/operators/depthwise_conv_op.cpp

@@ -14,7 +14,6 @@ limitations under the License. */
 
 #include "operators/depthwise_conv_op.h"
 #include <vector>
-#include "framework/data_type.h"
 #include "framework/op_proto_maker.h"
 #include "framework/op_registry.h"
 #include "operators/conv_op.h"

src/operators/kernel/arm/sigmoid_kernel.cpp

@@ -25,35 +25,21 @@ using framework::Tensor;
 
 void sigmoid(const Tensor *X, Tensor *Y) {
 #if __ARM_NEON
-  DLOG << "step1";
   const float *input = X->data<float>();
-  DLOG << "step11";
-
   float *output = Y->mutable_data<float>();
-  DLOG << "step2";
-
   const DDim &dDim = X->dims();
-  DLOG << "step3";
-
   int axis_index = 1;
   if (dDim.size() < 4) {
     axis_index = 0;
   }
-  DLOG << "step4";
-
   DDim outer_ddim =
       paddle_mobile::framework::slice_ddim(dDim, 0, axis_index + 1);
   DDim inner_ddim =
       paddle_mobile::framework::slice_ddim(dDim, axis_index + 1, dDim.size());
-  DLOG << "step5";
-
   int out_size = paddle_mobile::framework::product(outer_ddim);
   int inner_size = paddle_mobile::framework::product(inner_ddim);
-  DLOG << "step6";
 
 #pragma omp parallel for
-  DLOG << "outsize=" << out_size;
-  DLOG << "innersize=" << inner_size;
   for (int i = 0; i < out_size; ++i) {
     const float *input_outer_ptr = input + i * inner_size;
     float *output_outer_ptr = output + i * inner_size;