def TrueBoolAttr : AttrConstraint<CPred<"$_self.cast<BoolAttr>().getValue()">>;

def CastValueToI64: NativeCodeCall<
  "CastValueToI64($0.getLoc(), $1, &$_builder)">;

def CastValueToElementType: NativeCodeCall<
  "$_builder.create<ConvertOp>($0.getLoc(), $1, "
  "getElementTypeOrSelf($2.getType()))">;

// Here, $0 is an ElementsAttr with exactly one element of type integer. $1 is

                             TF_Status* status) {
  auto* cc_builder = reinterpret_cast<OpDefBuilder*>(builder);
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::OpRegistry::Global()->Register(
      [cc_builder](::tensorflow::OpRegistrationData* op_reg_data) -> Status {
        Status result = cc_builder->Finalize(op_reg_data);
        delete cc_builder;
        return result;
      });
}

  NativeCodeCall<"GetI64ElementsAttr({" # value # "}, &$_builder)">;

class GetF32Scalar<int value> :
  NativeCodeCall<"GetF32Scalar(&$_builder, " # value # ")">;

def TrueBoolAttr : AttrConstraint<CPred<"$_self.cast<::mlir::BoolAttr>().getValue()">>;

def CreateTFShapeOp : NativeCodeCall<
    "$_builder.create<TF::ShapeOp>($0.getLoc(), $1, $2)">;

def IsI32 : NativeCodeCall<

				MatchingPrecedence: matchingPrecedence,
			},
		},
	}
}

func (b *fsBuilder) Object() *flowcontrolv1.FlowSchema {
	return b.object
}

func (b *fsBuilder) WithGeneration(value int64) *fsBuilder {
	b.object.SetGeneration(value)
	return b
}

func (b *fsBuilder) WithAutoUpdateAnnotation(value string) *fsBuilder {
	setAnnotation(b.object, value)
	return b
}

def convertIntAttrTo32Bit : NativeCodeCall<
    "$_builder.getI32IntegerAttr($0.cast<IntegerAttr>().getInt())">;

// Builds a constant bool attribute.
class GetBoolAttr<int value> :
    NativeCodeCall<"$_builder.getBoolAttr(" # value #")">;

// Converts an integer attribute $0 to 64-bit with builder.
def convertIntAttrTo64Bit : NativeCodeCall<
    "$_builder.getI64IntegerAttr($0.cast<IntegerAttr>().getInt())">;

    void (*compute_func)(void*, TF_OpKernelContext*),
    void (*delete_func)(void*)) {
  TF_KernelBuilder* result = new TF_KernelBuilder;
  result->cc_builder = new ::tensorflow::KernelDefBuilder(op_name);
  result->cc_builder->Device(device_name);
  result->create_function = create_func;
  result->compute_function = compute_func;
  result->compute_async_function = nullptr;
  result->delete_function = delete_func;

  CPred<"$_self.isa<DenseElementsAttr>()">,
  "non-opaque constant tensor">;

def CreateGatherNdOp : NativeCodeCall<
    "$_builder.create<TF::GatherNdOp>($0.getLoc(), $0.getType(), $1, $2)">;

def CreateTFCastOpI32 : NativeCodeCall<
    "CreateTFCastOpI32(&$_builder, $_loc, $0, $1)">;

// Convert to std constant for statically shaped, non-opaque constants.

  auto resultType =
      OpTrait::util::getBroadcastedType(x.getType(), y.getType());
  if (!resultType) {
    mlir::emitError($_state.location, "non-broadcastable operands");
    resultType = $_builder.getNoneType();
  }
  return build($_builder, $_state, resultType, x, y);
}]>];
}

// Mixin class defining a builder for comparison ops supporting broadcast
// behavior. The result type has bool element type.

// Return intermediate shape before broadcasting, wrapped in a constant op.
def ExpandedShape : NativeCodeCall<"ExpandedShape($_builder, $0, $1, $2)">;
def ExpandedDynamicShape : NativeCodeCall<"ExpandedDynamicShape($_builder, $0, $1, $2)">;

def : Pat<(MHLO_ConstantOp:$output $value), (TF_ConstOp $value),
          [(TF_Tensor $output)]>;

}

// Control type.
def TfeControlType : Type<CPred<"$_self.isa<ControlType>()">, "control">,
                     BuildableType<"$_builder.getType<ControlType>()">;

// Token type.
def TfeTokenType : Type<CPred<"$_self.isa<TokenType>()">, "token">,
                   BuildableType<"$_builder.getType<TokenType>()">;

// TODO(hinsu): Define and use TensorType instead of AnyType for data operands