namespace TF {

// This all moved under tensorflow/core/ir/types and these using declaration are
// to help with the transition.

using ::mlir::tf_type::AreCastCompatible;          // NOLINT
using ::mlir::tf_type::ArraysAreCastCompatible;    // NOLINT
using ::mlir::tf_type::BroadcastCompatible;        // NOLINT
using ::mlir::tf_type::DropRefType;                // NOLINT
using ::mlir::tf_type::filter_resources;           // NOLINT

    // InferTypeOpInterface:
    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
      return ArraysAreCastCompatible(l, r);
    }
  }];

  let extraClassDeclaration = [{
    static bool isCompatibleReturnTypes(TypeRange inferred, TypeRange actual) {
      return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_ExtractImagePatchesOp : TF_Op<"ExtractImagePatches", [Pure]> {

  let extraClassDeclaration = [{
    // Returns whether the return types are compatible.
    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
      return TF::ArraysAreCastCompatible(l, r);
    }
  }];
}

def TFL_ConcatenationOp : TFL_Op<"concatenation",
  [
    Pure,
    TFL_SameFirstOperandAndFirstResultElementType,
    SameOperandsAndResultsScale,

  let hasCanonicalizer = 1;

  let extraClassDeclaration = [{
    // InferTypeOpInterface:
    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
      return ArraysAreCastCompatible(l, r);
    }
  }];
}

def TF_BesselI0eOp : TF_Op<"BesselI0e", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes the Bessel i0e function of `x` element-wise.";