}

func.func @real(%arg0: tensor<1 x complex<f64>>) -> tensor<1xf64> {
  %0 = "tf.Real"(%arg0) : (tensor<1 x complex<f64>>) -> tensor<1xf64>
  func.return %0: tensor<1xf64>

// CHECK-LABEL: real
// CHECK:  "tfl.real"(%arg0) : (tensor<1xcomplex<f64>>) -> tensor<1xf64>
// CHECK:  return
}

func.func @imag(%arg0: tensor<1 x complex<f64>>) -> tensor<1xf64> {

func.func @stridedSliceGrad(%dy: tensor<4x8xf32>, %begin: tensor<2xi64>, %end: tensor<2xi64>, %strides: tensor<2xi64>, %shape: tensor<2xi64>) -> tensor<?x?xf32> {
  // CHECK: tf.StridedSliceGrad
  %0 = "tf.StridedSliceGrad"(%shape, %begin, %end, %strides, %dy) : (tensor<2xi64>, tensor<2xi64>, tensor<2xi64>, tensor<2xi64>, tensor<4x8xf32>) -> tensor<?x?xf32>
  func.return %0 : tensor<?x?xf32>
}

// -----

// CHECK:           [[VAL_62:%.*]] = "tf.Slice"([[VAL_53]], [[VAL_60]], [[VAL_61]]) : (tensor<4x3xf32>, tensor<2xi64>, tensor<2xi64>) -> tensor<1x0xf32>
// CHECK-DAG:       [[VAL_63:%.*]] = arith.constant dense<[2, 0]> : tensor<2xi64>
// CHECK-DAG:       [[VAL_64:%.*]] = arith.constant dense<[1, 0]> : tensor<2xi64>
// CHECK:           [[VAL_65:%.*]] = "tf.Slice"([[VAL_53]], [[VAL_63]], [[VAL_64]]) : (tensor<4x3xf32>, tensor<2xi64>, tensor<2xi64>) -> tensor<1x0xf32>

  func.func @map_outside_compilation_0_inputs(%arg0 : tensor<2xi64>) -> () {
    // CHECK:             "tf._XlaHostComputeMlir"()
    "tf_device.cluster"() ({
      %1 = "tf.OpA"(%arg0) {_xla_map_outside_compilation = "0", _xla_outside_compilation = "from_launch"} : (tensor<2xi64>) -> tensor<2xi64>
      "tf.OpB"(%1) : (tensor<2xi64>) -> ()
      tf_device.return

  func.return %3 : tensor<2xi64>
  // CHECK: %[[CST:.*]] = "tf.Const"() <{value = dense<[1, 2]> : tensor<2xi64>}> : () -> tensor<2xi64>
  // CHECK: return %[[CST]]
}

// CHECK-LABEL: testFoldStridedSliceShapeDynamicOutput

  func.return %0 : tensor<3xf32>
}

// -----

// CHECK-LABEL: testReal
func.func @testReal(%arg0: tensor<? x complex<f64>>) -> tensor<?xf64> {
  // CHECK: "tfl.real"(%arg0)
  %0 = "tfl.real"(%arg0): (tensor<? x complex<f64>>) -> tensor<?xf64>
  func.return %0 : tensor<?xf64>
}

// -----

func.func @testRealWrongShape(%arg0: tensor<3 x complex<f64>>) -> tensor<4xf32> {

// CHECK: %[[MAX:.+]] = "tfl.maximum"(%[[CONCAT]], %[[ZERO]]) : (tensor<2xi64>, tensor<1xi64>) -> tensor<2xi64>
// CHECK: %[[SLICE:.+]] = "tfl.slice"(%[[ARG0]], %[[MAX]], %[[SLICE_SIZE]])
// CHECK-SAME: (tensor<4x4x!quant.uniform<i8:f32, 3.000000e-01:-5>>, tensor<2xi64>, tensor<2xi64>) -> tensor<2x1x!quant.uniform<i8:f32, 3.000000e-01:-5>>

// -----

    // CHECK-NOT: tensor<?xf64>
    func.return %0 : tensor<?xf64>
  }

  // CHECK-LABEL: set_dynamic_dimension_size_static_dim
  func.func @set_dynamic_dimension_size_static_dim(%input: tensor<4x5xf32>, %size: tensor<i32>) -> tensor<*xf32> {