// CHECK:  return
}

func.func @pow(%arg0: tensor<2x1x3xf32>, %arg1: tensor<2x1x1xf32>) -> tensor<2x1x3xf32> {
  %0 = "tf.Pow"(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32>
  func.return %0 : tensor<2x1x3xf32>

  // CHECK-LABEL: pow
  // CHECK:  %[[pow:.*]] = tfl.pow(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32>
  // CHECK:  return
}

  %2 = "tf.Const"() {value = dense<[2, 4, 4, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
  %3 = "tf.Sub"(%0, %arg1) {device = ""} : (tensor<1x4x4x2xf32>, tensor<2x4x4x2xf32>) -> tensor<2x4x4x2xf32>
  %4 = "tf.Reshape"(%3, %1) {device = ""} : (tensor<2x4x4x2xf32>, tensor<3xi32>) -> tensor<2x16x2xf32>

      %2 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<1x8x2xi32>) -> tensor<1x8x2xf32>
      tf_device.return %2 : tensor<1x8x2xf32>
    // CHECK: () -> tensor<1x8x2xf32>
    }) {device = "/device:CPU:0"} : () -> tensor<*xf32>
    // CHECK: "tf.Cast"(%{{.*}}) <{Truncate = false}> : (tensor<1x8x2xf32>) -> tensor<*xf32>
    // CHECK: (tensor<i32>, tensor<1x8x2xf32>) -> (tensor<1x8x1xf32>, tensor<1x8x1xf32>)

}

// -----

// CHECK-LABEL: topk_2
func.func @topk_2(%arg0: tensor<3x4x8xf32>) -> (tensor<3x4x2xf32>, tensor<3x4x2xi32>) {
  %0 = arith.constant dense<2> : tensor<i32>
  %1:2 = "tfl.topk_v2"(%arg0, %0) : (tensor<3x4x8xf32>, tensor<i32>) -> (tensor<3x4x2xf32>, tensor<3x4x2xi32>)
  func.return %1#0, %1#1: tensor<3x4x2xf32>, tensor<3x4x2xi32>
}

// -----

// CHECK-LABEL: topk_d

func.func @testReshapeNoOp(%arg0: tensor<2x4xf32>, %arg1: tensor<2xi32>) -> tensor<2x4xf32> {
  %0 = "tf.Reshape"(%arg0, %arg1) : (tensor<2x4xf32>, tensor<2xi32>) -> tensor<2x4xf32>

  // CHECK: return %arg0
  func.return %0 : tensor<2x4xf32>
}

// CHECK-LABEL: func @testBroadcastToNoOp
func.func @testBroadcastToNoOp(%arg0: tensor<2x4xf32>, %arg1: tensor<2xi32>) -> tensor<2x4xf32> {

func.func @testPackedTPUPartitionedInputV2(tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32> {
^bb0(%arg0: tensor<2x4xf32>, %arg1: tensor<2x4xf32>):
  // expected-error @+1 {{expected 1 inputs, got 2}}
  %0 = "tf.TPUPartitionedInputV2"(%arg0, %arg1) {partition_dims = [2, 1], is_packed = true} : (tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32>
  func.return %0 : tensor<4x4xf32>
}

// -----

    return success();
  }
};

// Fuses Unpack with proceeding Concatenation to Reshape if output type has
// static shape and activation function is none. For example:
//
//   // %input: tensor<1x3x2xf32>
//   %unpack:3 = "tfl.unpack"(%input) {axis = 1 : i32, num = 3 : i32}
//   %res = "tfl.concatenation"(%unpack#0, %unpack#1, %unpack#2)
//        {axis = -1 : i32, fused_activation_function = "NONE"}
//