}

func.func @cast(%arg0: tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32> {
  %0 = "tf.Cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
  func.return %0 : tensor<1x2x2x5xf32>

  // CHECK-LABEL: cast
  // CHECK: "tfl.cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
}

func.func @castFloat32ToI16(%arg0: tensor<1x2x2x5xf32>) -> tensor<1x2x2x5xi16> {

    %unshaped = "tf.Cast"(%arg1) : (tensor<1x2x3xf32>) -> tensor<*xf32>
    // CHECK: <{is_stateless = true}>
    %0 = "tf.IfRegion"(%arg0) <{is_stateless = true}> ({
      // CHECK: "tf.Add"{{.+}}(tensor<1x2x3xf32>, tensor<1x2x3xf32>) -> tensor<1x2x3xf32>
      // CHECK: "tf.Yield"{{.+}}(tensor<1x2x3xf32>) -> ()

func.func @testBatchMatMulV2PartiallyKnownInputBatchDim(%lhs: tensor<4x5x?x3x2xf32>, %rhs: tensor<1x1x3x5xf32>) -> (tensor<4x5x?x2x5xf32>) {
  %0 = "tf.BatchMatMulV2"(%lhs, %rhs) { adj_x = true } : (tensor<4x5x?x3x2xf32>, tensor<1x1x3x5xf32>) -> tensor<4x5x?x2x5xf32>
  func.return %0 : tensor<4x5x?x2x5xf32>
}

// -----

// CHECK-LABEL: func @testBatchMatMulV2PartiallyKnownMatmulDim

// CHECK-LABEL: testConvertPackToReshapeAxis0
func.func @testConvertPackToReshapeAxis0(%arg0: tensor<2x3xf32>) -> tensor<1x2x3xf32> {
  %0 = "tf.Pack"(%arg0) {axis = 0 : i64, _xla_outside_compilation = "1", device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<2x3xf32>) -> tensor<1x2x3xf32>
  func.return %0 : tensor<1x2x3xf32>
  // CHECK: %[[SHAPE:.*]] = "tf.Const"() <{value = dense<[1, 2, 3]> : tensor<3xi32>}> : () -> tensor<3xi32>

// CHECK-NEXT:    return %[[VAL_2]] : tensor<1x2x4x1xf32>
// CHECK-NEXT:  }
}

// -----

module {
// expected-warning @+1 {{Invalid number of results from MaxUnpooling2D}}

  // CHECK: "tfl.strided_slice"(%arg0, %arg1, %arg2, %arg3) <{begin_mask = 0 : i32, ellipsis_mask = 0 : i32, end_mask = 0 : i32, new_axis_mask = 0 : i32, offset = false, shrink_axis_mask = 0 : i32}> : (tensor<12x2x2x5xf32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x2x2x5xf32>