}

// 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),

func h3[P any](func(P), func(P), func() P)                   {}
func h4[P, Q any](func(P), func(P, Q), func() Q, func(P, Q)) {}

func r1() int { return 0 }

func _() {
	h3(g1, g1, r1)
	h4(g1, g2, r1, g2)
}

// Variadic cases

func f(func(int))
func g[P any](P) {}

func d[P any](...func(P)) {}

func _() {
	d /* ERROR "cannot infer P" */ ()
	d(f)
	d(f, g)
	d(f, g, g)
	d /* ERROR "cannot infer P" */ (g, g, g)

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()">;

      } : (!tfrt.chain, !tfd.tf_tensor, !tfd.tf_tensor) -> (
        !tfrt.chain, !tfd.tf_tensor)
  }];

  let arguments = (ins TFRT_ChainType, Variadic<AnyType>);
  let results = (outs TFRT_ChainType, Variadic<AnyType>);
}

def PrintTftOp : RuntimeFallbackDialect_Op<"print_tft"> {
  let summary = "print TF tensor operation";
  let description = [{

    quantized kernel.
  }];

  let arguments = (ins Variadic<AnyType>:$inputs,
                    TypeArrayAttr:$input_specs,
                    TypeArrayAttr:$output_specs,
                    StrAttr:$logical_kernel);
  let results = (outs Variadic<AnyType>:$outputs);
  let regions = (region SizedRegion<1>:$body);
  let hasVerifier = 1;
}

    quantized kernel.
  }];

  let arguments = (ins Variadic<AnyType>:$inputs,
                    TypeArrayAttr:$input_specs,
                    TypeArrayAttr:$output_specs,
                    StrAttr:$logical_kernel);
  let results = (outs Variadic<AnyType>:$outputs);
  let regions = (region SizedRegion<1>:$body);
  let hasVerifier = 1;
}

    the `call` operation can only be with tfr.tensor and tfr.tensor_list types.
  }];

  let arguments = (ins
    FlatSymbolRefAttr:$callee,
    Variadic<TFR_allowedArgType>:$args);

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

  let extraClassDeclaration = [{
    // Get the argument operands to the called function.
    operand_range getArgOperands() { return getArgs(); }

	// --------------+------------------+----------------+
	// variadic func | nargs >= npars-1 | nargs == npars |
	// --------------+------------------+----------------+

	nargs := len(args)
	npars := sig.params.Len()
	ddd := hasDots(call)

	// set up parameters
	sigParams := sig.params // adjusted for variadic functions (may be nil for empty parameter lists!)

type someStruct struct{}

// Log is non-variadic user-define Println-like function.
// Calls to this func must be skipped when checking
// for Println-like arguments.
func (ss *someStruct) Log(f func(), s string) {}

// Error is variadic user-define Println-like function.
// Calls to this func mustn't be checked for Println-like arguments,
// since variadic arguments type isn't interface{}.