// CHECK:  %cst = arith.constant dense<2> : tensor<1xi32>
  // CHECK:  %4 = "tfl.reduce_min"(%arg0, %cst) <{keep_dims = false}> : (tensor<4x32x256xf32>, tensor<1xi32>) -> tensor<4x32xf32>
  // CHECK:  %5 = "tfl.arg_min"(%arg0, %cst) : (tensor<4x32x256xf32>, tensor<1xi32>) -> tensor<4x32xi32>
  // CHECK:  return %4, %5 : tensor<4x32xf32>, tensor<4x32xi32>
}

// CHECK-LABEL:   func @convert_argmin_i16

    func.return %0 : tensor<2x5xi32>
  }

  // CHECK-LABEL: arg_min
  func.func @arg_min(%arg0: tensor<6xf64>) -> tensor<i32> {
    // CHECK-NOT: ArgMin
    %0 = mhlo.constant dense<0> : tensor<i32>
    %1 = "tf.ArgMin"(%arg0, %0) : (tensor<6xf64>, tensor<i32>) -> tensor<i32>
    func.return %1 : tensor<i32>
  }

  // CHECK-LABEL: non_max_suppression_v4

  TILE = 69,
  EXPAND_DIMS = 70,
  EQUAL = 71,
  NOT_EQUAL = 72,
  LOG = 73,
  SUM = 74,
  SQRT = 75,
  RSQRT = 76,
  SHAPE = 77,
  POW = 78,
  ARG_MIN = 79,
  FAKE_QUANT = 80,
  REDUCE_PROD = 81,
  REDUCE_MAX = 82,
  PACK = 83,
  LOGICAL_OR = 84,
  ONE_HOT = 85,
  LOGICAL_AND = 86,
  LOGICAL_NOT = 87,
  UNPACK = 88,
  REDUCE_MIN = 89,
  FLOOR_DIV = 90,

  TILE = 69,
  EXPAND_DIMS = 70,
  EQUAL = 71,
  NOT_EQUAL = 72,
  LOG = 73,
  SUM = 74,
  SQRT = 75,
  RSQRT = 76,
  SHAPE = 77,
  POW = 78,
  ARG_MIN = 79,
  FAKE_QUANT = 80,
  REDUCE_PROD = 81,
  REDUCE_MAX = 82,
  PACK = 83,
  LOGICAL_OR = 84,
  ONE_HOT = 85,
  LOGICAL_AND = 86,
  LOGICAL_NOT = 87,
  UNPACK = 88,
  REDUCE_MIN = 89,
  FLOOR_DIV = 90,

  TILE = 69,
  EXPAND_DIMS = 70,
  EQUAL = 71,
  NOT_EQUAL = 72,
  LOG = 73,
  SUM = 74,
  SQRT = 75,
  RSQRT = 76,
  SHAPE = 77,
  POW = 78,
  ARG_MIN = 79,
  FAKE_QUANT = 80,
  REDUCE_PROD = 81,
  REDUCE_MAX = 82,
  PACK = 83,
  LOGICAL_OR = 84,
  ONE_HOT = 85,
  LOGICAL_AND = 86,
  LOGICAL_NOT = 87,
  UNPACK = 88,
  REDUCE_MIN = 89,
  FLOOR_DIV = 90,

type instArg uint16

const (
	_ instArg = iota
	arg_Bt
	arg_Cm
	arg_Cn
	arg_cond_AllowALNV_Normal
	arg_conditional
	arg_cond_NotAllowALNV_Invert
	arg_Da
	arg_Dd
	arg_Dm
	arg_Dn
	arg_Dt
	arg_Dt2
	arg_Hd
	arg_Hn
	arg_Ht
	arg_IAddSub
	arg_immediate_0_127_CRm_op2
	arg_immediate_0_15_CRm
	arg_immediate_0_15_nzcv

                                                int argument_index,
                                                TaggedValue& args_in,
                                                TArgsOut... args) {
    Handle h(std::move(args_in.tuple()[argument_index]));
    tensorflow::StatusOr<TSignatureArg> x = Cast<TSignatureArg>(std::move(h));
    if (!x.ok())
      return absl::InvalidArgumentError(

      auto arg_it = info.stack_var_arg_to_size_arg.find(i);
      if (arg_it == info.stack_var_arg_to_size_arg.end()) continue;
      auto it = data_var_to_size_var.find(call.getOperand(i));
      if (it == data_var_to_size_var.end()) {
        call.emitOpError("unknown stack");
        return failure();
      }
      assert(arg_it->second == new_operands.size());

  %2 = "tfl.dequantize"(%1) : (tensor<128x16x!quant.uniform<u8:f32, 3.906250e-03>>) -> tensor<128x16xf32>
// CHECK-NEXT:  %[[argmax:.*]] = "tfl.arg_max"(%[[softmax]], %[[cst]]) : (tensor<128x16xf32>, tensor<i32>) -> tensor<128xi32>
  %3 = "tfl.arg_max"(%2, %cst) : (tensor<128x16xf32>, tensor<i32>) -> tensor<128xi32>
// CHECK-NEXT:  return %[[softmax]], %[[argmax]] : tensor<128x16xf32>, tensor<128xi32>

	arg_R_0
	arg_R_12
	arg_R_12_nzcv
	arg_R_16
	arg_R_16_WB
	arg_R_8
	arg_R_rotate
	arg_R_shift_R
	arg_R_shift_imm
	arg_SP
	arg_Sd
	arg_Sd_Dd
	arg_Dd_Sd
	arg_Sm
	arg_Sm_Dm
	arg_Sn
	arg_Sn_Dn
	arg_const
	arg_endian
	arg_fbits
	arg_fp_0
	arg_imm24
	arg_imm5
	arg_imm5_32
	arg_imm5_nz
	arg_imm_12at8_4at0
	arg_imm_4at16_12at0
	arg_imm_vfp
	arg_label24