(MHLO_CompositeOp:$composite
          (variadic $inputs),
          ConstantStrAttr<StrAttr, "aten.gelu.default">, $attrs, $_, $_),
        (TFL_GeluOp $inputs, ConstBoolAttrFalse),
        [(IsStrCompositeAttribute<"approximate", "none"> $attrs)]>;

def LegalizeCompositeApproximateAtenGELU : Pat<
        (MHLO_CompositeOp:$composite
          (variadic $inputs),

  }];

  let arguments = (ins
    TF_Tensor:$max_iterations,
    Variadic<TF_Tensor>:$tensor_list_or_flow_in,
    Variadic<TF_Tensor>:$invariant_args,
    FlatSymbolRefAttr:$body_fn,
    I32Attr:$num_tensor_list_or_flow_in
  );

  let results = (outs
     Variadic<TF_Tensor>:$result
  );

    element of `args` is a key to a loaded array corresponding to a variable.
  }];

  let arguments = (ins
    Variadic<TF_Tensor> : $args,
    I64Attr : $program_id,
    I32ArrayAttr : $variable_arg_indices
  );

  let results = (outs Variadic<TF_Tensor> : $results);

  TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<0>;

// ops that match the behaviour of tfl.average_pool_2d are directly lowered.
def LegalizeAvgPool2dComposite: Pat<
                    (MHLO_CompositeOp:$old_val
                    (variadic $a_input), 
                    ConstantStrAttr<StrAttr, "aten.avg_pool2d.default">, $attrs, $_, $_),
                    (TFL_TransposeOp 
                        (TFL_AveragePool2DOp 

  }];

  let arguments = (ins
    Variadic<TFTensorType>:$operands,
    StrAttr:$func_name,
    I64ArrayAttr:$resource_indices,
    I64ArrayAttr:$used_output_indices
  );
  let results = (outs
    Variadic<TFTensorType>:$results
  );
}

  }];
  let arguments = (ins
    Variadic<TFTensorType>:$operands_and_static_shapes,
    DenseI32ArrayAttr:$constant_operand_indices,
    StrAttr:$metadata,
    StrAttr:$mlir_module,
    UI32Attr:$num_operands,
    DenseI32ArrayAttr:$operands_with_static_shape,
    StrAttr:$producer_name
  );

  let results = (outs
    TFTensorType:$rendezvous_key_base,
    Variadic<MlrtFutureType>:$results
  );

//
// The implementation fn can assume that the argument [Value] slice
// has the number and type of arguments given by typ.
// If typ describes a variadic function, the final Value is itself
// a slice representing the variadic arguments, as in the
// body of a variadic function. The result Value slice returned by fn
// must have the number and type of results given by typ.
//

}

// Min returns the minimum element of `nums`.
func Min[T IntLike, NumSlice ~[]T](nums NumSlice) T {
	if len(nums) == 0 {
		return T(0)
	}
	return Reduce(min[T], nums, nums[0])
}

// VarMin is the variadic version of Min.
func VarMin[T IntLike](nums ...T) T {
	return Min(nums)
}

type myInt int

func main() {
	fmt.Println(VarMin(myInt(1), myInt(2)))

	seq := []myInt{1, 2}
	fmt.Println(Min(seq))

>;

// Removes `stablehlo.custom_call @Sharding`. Assumes this call always accepts
// one input. Other attributes are ignored.
def RemoveShardingCustomCall : Pat<
  (StableHLO_CustomCallOp (variadic $input0), $call_target_name, $_, $_, $_, $_, $_, $_, $_),
  (replaceWithValue $input0),

include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"
include "mlir/IR/OpBase.td"
include "mlir/IR/PatternBase.td"
include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.td"

// Combines the two variadic arguments ($in_tensors and $captured_tensors).
def GetBatchFunctionOpArgOperands:
    NativeCodeCall<"cast<TF::BatchFunctionOp>($0[0].getDefiningOp()).getArgOperands()">;