AutoMappingByOpFn

Function Usage

The callback function that implements automatic mapping.

Prototype

      
           Status AutoMappingByOpFn(const ge::Operator &op_src, ge::Operator &op);

Parameters

Parameter	Input/Output	Description
op_src	Input	Operator in the original model before conversion, including the attributes of the operator in the original model.
op	Input	Operator that adapts to AI processor.

For details about class Operator, see Operator.

Examples

The following describes the scenario where the attributes of the original TensorFlow operator are one-to-one mapped to those of the equivalent supported by AI processor.

      
           REGISTER_CUSTOM_OP("SoftplusGrad")
.FrameworkType(TENSORFLOW)
.OriginOpType("SoftplusGrad")
.ParseParamsByOperatorFn(AutoMappingByOpFn)
.ImplyType(ImplyType::TVM);

The following describes the scenario where the attributes of the original TensorFlow operator cannot be mapped to those of the equivalent supported by AI processor.

      
       
         
         
           Status ParseResizeArea(const ge::Operator &op_src, ge::Operator& op)
  {
    AutoMappingByOpFn(op_src, op);

    ge::TensorDesc input_tensor = op.GetInputDesc("images");
    input_tensor.SetOriginFormat(ge::FORMAT_NHWC);
    input_tensor.SetFormat(ge::FORMAT_NHWC);
    auto ret = op.UpdateInputDesc("images", input_tensor);
    if(ret != ge::GRAPH_SUCCESS){
        return FAILED;
    }
    ge::TensorDesc output_tensor = op.GetOutputDesc("y");
    output_tensor.SetOriginFormat(ge::FORMAT_NHWC);
    output_tensor.SetFormat(ge::FORMAT_NHWC);
    auto ret_output = op.UpdateOutputDesc("y", output_tensor);
    if(ret_output != ge::GRAPH_SUCCESS){
        return FAILED;
    }
    return SUCCESS;
  }
// register ResizeArea op to GE
REGISTER_CUSTOM_OP("ResizeArea")
  .FrameworkType(TENSORFLOW)
  .OriginOpType("ResizeArea")
  .ParseParamsByOperatorFn(ParseResizeArea)
  .ImplyType(ImplyType::AI_CPU);

          

        

      
     

Parent topic: OpRegistrationData