// Unsupported strides
  %2 = "tf.MaxPool"(%arg0) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", ksize = [1, 3, 6, 1], padding = "VALID", strides = [1, 3, 1, 3]} : (tensor<1x1x1x16xf32>) -> tensor<1x1x1x16xf32>

  %5 = arith.addf %0, %1 : tensor<1x1x1x16xf32>
  %6 = arith.addf %2, %5 : tensor<1x1x1x16xf32>
  func.return %6 : tensor<1x1x1x16xf32>

^bb0(%arg0: tensor<1x7x7x16xf32>):
  // expected-error @+1 {{requires attribute 'padding'}}
  %0 = "tf.AvgPool"(%arg0) {T = "tfdtype$DT_FLOAT", ksize = [1, 7, 7, 1], strides = [1, 1, 1, 1]} : (tensor<1x7x7x16xf32>) -> tensor<1x1x1x16xf32>
  func.return %0 : tensor<1x1x1x16xf32>
}

// -----

func.func @testAvgPoolWrongPadding(tensor<1x7x7x16xf32>) -> tensor<1x1x1x16xf32> {

}

// -----

func.func @sub_with_quantized_i8_five_dim_broadcasting(tensor<1x1x1x1x1xf32>, tensor<1xf32>) -> tensor<1x1x1x1x1x!quant.any<i8:f32>> {
^bb0(%arg0: tensor<1x1x1x1x1xf32>, %arg1: tensor<1xf32>):
  %0 = "tfl.sub"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1x1x1x1x1xf32>, tensor<1xf32>) -> tensor<1x1x1x1x1x!quant.any<i8:f32>>
  func.return %0#0 : tensor<1x1x1x1x1x!quant.any<i8:f32>>
}