// This file defines some basic elements of Paddle(alias trt) dialect. // We learned much from TensorFlow mlir dialect https://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td #ifndef TRT_OP_BASE #define TRT_OP_BASE include "mlir/IR/OpBase.td" include "mlir/Interfaces/SideEffectInterfaces.td" def TRT_Dialect : Dialect { let name = "trt"; let description = [{ The PaddlePaddle dialect. This dialect contains the PaddlePaddle operators. }]; let cppNamespace = "::infrt::trt"; } class TRT_Op traits = []> : Op; class TRT_PaddleAttr : Attr()">, "PaddlePaddle " # description # " attribute">; //===----------------------------------------------------------------------===// // PaddlePaddle type definitions //===----------------------------------------------------------------------===// def TRT_TRTDialectType : Type()">, "PaddlePaddle type">; class TRT_PaddleType : Type()">, "Paddle " # description # " type">, BuildableType<"getType()">; //===----------------------------------------------------------------------===// // Integer types def TRT_Bool : AnyTypeOf<[I<1>], "bool">; def TRT_Int8 : AnyTypeOf<[I8], "8-bit integer">; def TRT_Int16 : AnyTypeOf<[I16], "16-bit integer">; def TRT_Int32 : AnyTypeOf<[I32], "32-bit integer">; def TRT_Int64 : AnyTypeOf<[I64], "64-bit integer">; def TRT_UInt8 : AnyTypeOf<[UI<8>], "8-bit unsigned integer">; def TRT_UInt16 : AnyTypeOf<[UI<16>], "16-bit unsigned integer">; def TRT_UInt32 : AnyTypeOf<[UI<32>], "32-bit unsigned integer">; def TRT_UInt64 : AnyTypeOf<[UI<64>], "64-bit unsigned integer">; def TRT_SInt : AnyTypeOf<[TRT_Int8, TRT_Int16, TRT_Int32, TRT_Int64], "signed integer">; def TRT_UInt : AnyTypeOf<[TRT_UInt8, TRT_UInt16, TRT_UInt32, TRT_UInt64], "unsigned integer">; def TRT_Int : AnyTypeOf<[TRT_SInt, TRT_UInt], "integer">; // Float types def TRT_Float16 : AnyTypeOf<[F16], "16-bit float">; def TRT_Float32 : AnyTypeOf<[F32], "32-bit float">; def TRT_Float64 : AnyTypeOf<[F64], "64-bit float">; def TRT_Float : AnyTypeOf<[TRT_Float16, TRT_Float32, TRT_Float64], "floating-point">; // Tensor types def TRT_ElementType : Type, "trt.dtype">; def TRT_Tensor : TensorOf<[TRT_ElementType]>; #endif // TRT_OP_BASE