func.return %0 : tensor<4xi8>
}

func.func @i16() -> tensor<4xi16> {
  // CHECK-LABEL: @i16
  // CHECK: value = dense<[1, 2, 3, 258]> : tensor<4xi16>
  %0 = "tfl.pseudo_const" () { value = dense<[1, 2, 3, 258]> : tensor<4xi16> } : () -> tensor<4xi16>
  func.return %0 : tensor<4xi16>
}

func.func @i32() -> tensor<4xi32> {
  // CHECK-LABEL: @i32

  func.return %0 : tensor<4xi8>
}

func.func @i16() -> tensor<4xi16> {
  // CHECK-LABEL: @i16
  // CHECK: value = dense<[1, 2, 3, 258]> : tensor<4xi16>
  %0 = "tfl.pseudo_const" () { value = dense<[1, 2, 3, 258]> : tensor<4xi16> } : () -> tensor<4xi16>
  func.return %0 : tensor<4xi16>
}

func.func @i32() -> tensor<4xi32> {
  // CHECK-LABEL: @i32

  %8 = "tfl.mul"(%2, %3) {fused_activation_function = "NONE"} : (tensor<4xf16>, tensor<4xf16>) -> tensor<4xf16>

  func.return %5, %6, %7, %8 : tensor<f16>, tensor<4xf16>, tensor<4xf16>, tensor<4xf16>
}

// CHECK-LABEL: @elementwise_unary_ops
func.func @elementwise_unary_ops() -> (tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>) {

  %15 = mhlo.compare  LT, %13, %14,  SIGNED : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1>
  %16 = "mhlo.broadcast_in_dim"(%0) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<i32>) -> tensor<4xi32>
  %17 = mhlo.add %13, %16 : tensor<4xi32>
  %18 = mhlo.select %15, %17, %13 : tensor<4xi1>, tensor<4xi32>

  // CHECK:  %cst = arith.constant dense<0> : tensor<1xi32>
  // CHECK:  %4 = "tfl.reduce_min"(%arg0, %cst) <{keep_dims = false}> : (tensor<2xi16>, tensor<1xi32>) -> tensor<i16>
  // CHECK:  %5 = "tfl.arg_min"(%arg0, %cst) : (tensor<2xi16>, tensor<1xi32>) -> tensor<i32>
  // CHECK:  return %4, %5 : tensor<i16>, tensor<i32>
}


// CHECK-LABEL: func @convert_argmin_constant