%4 = "tfl.conv_2d"(%arg0, %cst_2, %cst_1) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<3x15x14x3xf32>, tensor<8x3x3x3xf32>, tensor<8xf32>) -> tensor<3x15x14x8xf32>
  func.return %4 : tensor<3x15x14x8xf32>
}

// CHECK-NEXT:      inputs: [ 2, 3, 4 ],
// CHECK-NEXT:      outputs: [ 5 ],
// CHECK-NEXT:      builtin_options_type: Conv2DOptions,
// CHECK-NEXT:      builtin_options: {
// CHECK-NEXT:        stride_w: 2,
// CHECK-NEXT:        stride_h: 2
// CHECK-NEXT:      }
// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 2,
// CHECK-NEXT:      inputs: [ 5, 1 ],
// CHECK-NEXT:      outputs: [ 6 ]
// CHECK-NEXT:    }, {

    } : (tensor<1x224x224x3xf32>) -> tensor<1x224x224x3xf32>
  %6 = "tfl.conv_2d"(%5, %4, %cst) {
      dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32

// CHECK:           %[[VAL_5:.*]] = "tfl.average_pool_2d"(%[[VAL_4]]) <{filter_height = 3 : i32, filter_width = 3 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 1 : i32, stride_w = 1 : i32}> : (tensor<1x6x6x3xf32>) -> tensor<1x4x4x3xf32>
// CHECK:           %[[VAL_6:.*]] = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>

  %1 = "tfl.relu"(%0) : (tensor<1x73x73x16xf32>) -> tensor<1x73x73x16xf32>
  func.return %1 : tensor<1x73x73x16xf32>

  %3 = "tfl.conv_2d"(%0, %1, %2) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>, tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, tensor<32x!quant.uniform<i32:f32, 1.7052092479439231E-4>>) -> tensor<1x112x112x32x!quant.uniform<u8:f32,...

    %3 = "tfl.conv_2d"(%0, %1, %2) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3xf32>, tensor<32x3x3x3xf32>, tensor<32xf32>) -> tensor<1x112x112x32xf32>

  %cst = "tfl.no_value"() {value = unit} : () -> none
  %0 = "tfl.conv_2d"(%arg0, %arg1, %cst) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<128x32x32x3xf32>, tensor<32x1x1x3xf32>, none) -> tensor<128x32x32x32xf32>
  func.return %0 : tensor<128x32x32x32xf32>
}

// CHECK:  %8 = "tf.Conv2D"(%arg0, %arg1) <{data_format = "NHWC", dilations = [1, 1, 1, 1], padding = "SAME", strides = [2, 1, 1, 1]}> {T = "tfdtype$DT_FLOAT"} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x32x32x16xf32>
}

// CHECK-NEXT: tfr.return %[[bl]] : !tfr.tensor_list
}

// CHECK-LABEL: @tf__my_max_pool
tfr.func @tf__my_max_pool(%input_: !tfr.tensor, %stride_w: i64{tfr.name="stride_w"}, %stride_h: i64{tfr.name="stride_h"}) -> (!tfr.tensor) {
  %cst_1 = arith.constant 1 : i64
  %stride = "tfr.build_list"(%cst_1, %stride_w, %stride_h, %cst_1) : (i64, i64, i64, i64) -> !tfr.attr
  %filter = tfr.constant [1, 2, 2, 1] -> !tfr.attr
  %padding = tfr.constant "VALID" -> !tfr.attr