attrs=[
        'stride_w: int', 'stride_h: int', 'filter_width: int',
        'filter_height: int', 'padding: {"SAME", "VALID"}'
    ],
    derived_attrs=['T: {float, int8}'],
    outputs=['o: T'])
def _composite_max_pool(input_, stride_w, stride_h, filter_width, filter_height,
                        padding):
  ksize = [1, filter_width, filter_height, 1]
  strides = [1, stride_w, stride_h, 1]
  return tf.raw_ops.MaxPool(

  func.return %0 : tensor<1x1x1x512xf32>
}

// CHECK:       func @mean_4d_keepdim([[VAL_0:%.*]]: tensor<1x48x48x512xf32>) -> tensor<1x1x1x512xf32> {
// CHECK:           [[VAL_1:%.*]] = "tfl.average_pool_2d"([[VAL_0]]) <{filter_height = 48 : i32, filter_width = 48 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 1 : i32, stride_w = 1 : i32}> : (tensor<1x48x48x512xf32>) -> tensor<1x1x1x512xf32>

^bb0(%arg0: tensor<1x6x6x16xf32>):
  // CHECK: "tfl.average_pool_2d"(%{{.*}}) <{filter_height = 3 : i32, filter_width = 6 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 3 : i32, stride_w = 1 : i32}> : (tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32>

                                (Arith_ConstantOp
                                    ConstantAttr<RankedI32ElementsAttr<[4]>,"{0, 2, 3, 1}">)),
                            /*filter_height*/(GetI32At<0> (GetAsVectorAttr<"kernel_size"> $attrs)),
                            /*filter_width*/(GetI32At<1> (GetAsVectorAttr<"kernel_size"> $attrs)),
                            /*padding*/(GetAvgPoolOpPadAttr $old_val),

  TfLitePoolParams pool_params;

  llvm::SmallVector<int32_t, 2> pool_size;
  if (failed(GetIntegerArraySafe(&func_, attrs, "pool_size", &pool_size, 2))) {
    return failure();
  }
  pool_params.filter_height = pool_size[0];
  pool_params.filter_width = pool_size[1];

  // Retrieve strides.
  llvm::SmallVector<int32_t, 2> strides;
  if (failed(GetIntegerArraySafe(&func_, attrs, "strides", &strides, 2))) {