remove transpose half and add transpose before shape() for gpu runtime.

mace/core/net_def_adapter.cc

@@ -50,15 +50,6 @@ std::string TransformedName(const std::string &input_name,
   return ss.str();
 }
 
-#ifdef MACE_ENABLE_OPENCL
-bool TransformRequiredOp(const std::string &op_type) {
-  static const std::unordered_set<std::string> kNoTransformOp = {
-      "Shape", "InferConv2dShape"
-  };
-  return kNoTransformOp.count(op_type) == 0;
-}
-#endif  // MACE_ENABLE_OPENCL
-
 void BuildTransposeOpDef(
     const std::string &input_name,
     const std::string &output_name,
@@ -514,76 +505,73 @@ MaceStatus NetDefAdapter::AdaptMemoryType(
   // (only support one kind of memory type for multiple outputs)
   op_registry_->GetInOutMemoryTypes(op_def->type(), context);
 #ifdef MACE_ENABLE_OPENCL
-  // if op is memory-unused op, no transformation
-  if (TransformRequiredOp(op_def->type())) {
-    int input_size = op_def->input_size();
-    for (int i = 0; i < input_size; ++i) {
-      if (output_map->count(op_def->input(i)) == 0) {
-        MACE_CHECK(ws_->GetTensor(op_def->input(i)) != nullptr
-                       && ws_->GetTensor(op_def->input(i))->is_weight(),
-                   "Tensor ", op_def->input(i), " of ",
-                   op_def->name(), " not allocated");
-        continue;
-      }
-      auto &input_info = output_map->at(op_def->input(i));
-      // check whether to do transform
-      MemoryType src_mem_type = input_info.mem_type;
-      MemoryType dst_mem_type = context->GetInputMemType(i);
-      auto wanted_input_dtype = context->GetInputDataType(i);
-      if (src_mem_type != dst_mem_type ||
-          (input_info.dtype != wanted_input_dtype &&
-              (src_mem_type != MemoryType::CPU_BUFFER
-                  || dst_mem_type != MemoryType::CPU_BUFFER))) {
-        auto transformed_name = TransformedName(op_def->input(i),
-                                                "mem_type",
-                                                dst_mem_type);
-        // check whether the tensor has been transformed
-        if (transformed_set->count(transformed_name) == 0) {
-          VLOG(1) << "Add Transform operation " << op_def->name()
-                  << " to transform tensor "
-                  << op_def->input(i) << "', from memory type "
-                  << input_info.mem_type << " to "
-                  << dst_mem_type;
-          OperatorDef *transformed_op_def = target_net_def->add_op();
-          OpenCLUtil::BuildTransformOpDef(
-              op_def->input(i),
-              input_info.shape,
-              transformed_name,
-              wanted_input_dtype,
-              context->GetInputOpenCLBufferType(i),
-              dst_mem_type,
-              input_info.data_format,
-              transformed_op_def);
-          // set data format arg
-          SetProtoArg<int>(transformed_op_def,
-                           "data_format",
-                           static_cast<int>(input_info.data_format));
-          // set output memory type argument
-          SetProtoArg<int>(transformed_op_def,
-                           OutputMemoryTypeTagName(),
-                           dst_mem_type);
+  int input_size = op_def->input_size();
+  for (int i = 0; i < input_size; ++i) {
+    if (output_map->count(op_def->input(i)) == 0) {
+      MACE_CHECK(ws_->GetTensor(op_def->input(i)) != nullptr
+                     && ws_->GetTensor(op_def->input(i))->is_weight(),
+                 "Tensor ", op_def->input(i), " of ",
+                 op_def->name(), " not allocated");
+      continue;
+    }
+    auto &input_info = output_map->at(op_def->input(i));
+    // check whether to do transform
+    MemoryType src_mem_type = input_info.mem_type;
+    MemoryType dst_mem_type = context->GetInputMemType(i);
+    auto wanted_input_dtype = context->GetInputDataType(i);
+    if (src_mem_type != dst_mem_type ||
+        (input_info.dtype != wanted_input_dtype &&
+            (src_mem_type != MemoryType::CPU_BUFFER
+                || dst_mem_type != MemoryType::CPU_BUFFER))) {
+      auto transformed_name = TransformedName(op_def->input(i),
+                                              "mem_type",
+                                              dst_mem_type);
+      // check whether the tensor has been transformed
+      if (transformed_set->count(transformed_name) == 0) {
+        VLOG(1) << "Add Transform operation " << op_def->name()
+                << " to transform tensor "
+                << op_def->input(i) << "', from memory type "
+                << input_info.mem_type << " to "
+                << dst_mem_type;
+        OperatorDef *transformed_op_def = target_net_def->add_op();
+        OpenCLUtil::BuildTransformOpDef(
+            op_def->input(i),
+            input_info.shape,
+            transformed_name,
+            wanted_input_dtype,
+            context->GetInputOpenCLBufferType(i),
+            dst_mem_type,
+            input_info.data_format,
+            transformed_op_def);
+        // set data format arg
+        SetProtoArg<int>(transformed_op_def,
+                         "data_format",
+                         static_cast<int>(input_info.data_format));
+        // set output memory type argument
+        SetProtoArg<int>(transformed_op_def,
+                         OutputMemoryTypeTagName(),
+                         dst_mem_type);
 
-          // update tensor consumer information
-          output_map->at(op_def->input(i)).consumer_op_indices.push_back(
-              target_net_def->op_size() - 1);
+        // update tensor consumer information
+        output_map->at(op_def->input(i)).consumer_op_indices.push_back(
+            target_net_def->op_size() - 1);
 
-          // update output information map
-          output_map->emplace(
-              transformed_name,
-              InternalOutputInfo(
-                  dst_mem_type,
-                  context->GetInputDataType(i),
-                  input_info.data_format,
-                  input_info.shape,
-                  target_net_def->op_size() - 1));
-          // update tensor shape map
-          tensor_shape_map->emplace(transformed_name, input_info.shape);
-          // record transformed tensors
-          transformed_set->insert(transformed_name);
-        }
-        // update original op_def's input
-        op_def->set_input(i, transformed_name);
+        // update output information map
+        output_map->emplace(
+            transformed_name,
+            InternalOutputInfo(
+                dst_mem_type,
+                context->GetInputDataType(i),
+                input_info.data_format,
+                input_info.shape,
+                target_net_def->op_size() - 1));
+        // update tensor shape map
+        tensor_shape_map->emplace(transformed_name, input_info.shape);
+        // record transformed tensors
+        transformed_set->insert(transformed_name);
       }
+      // update original op_def's input
+      op_def->set_input(i, transformed_name);
     }
   }
 #else

mace/ops/transpose.cc

@@ -27,7 +27,10 @@ namespace mace {
 namespace ops {
 
 template<DeviceType D, typename T>
-class TransposeOp : public Operation {
+class TransposeOp;
+
+template<DeviceType D>
+class TransposeOp<D, float> : public Operation {
  public:
   explicit TransposeOp(OpConstructContext *context)
       : Operation(context),
@@ -49,8 +52,8 @@ class TransposeOp : public Operation {
 
     Tensor::MappingGuard input_guard(input);
     Tensor::MappingGuard output_guard(output);
-    const T *input_data = input->data<T>();
-    T *output_data = output->mutable_data<T>();
+    const float *input_data = input->data<float>();
+    float *output_data = output->mutable_data<float>();
 
     return Transpose(&context->device()->cpu_runtime()->thread_pool(),
                      input_data, input->shape(), dims_, output_data);
@@ -63,8 +66,6 @@ class TransposeOp : public Operation {
 void RegisterTranspose(OpRegistryBase *op_registry) {
   MACE_REGISTER_OP(op_registry, "Transpose", TransposeOp,
                    DeviceType::CPU, float);
-  MACE_REGISTER_OP(op_registry, "Transpose", TransposeOp,
-                   DeviceType::CPU, half);
 }
 
 }  // namespace ops