code: def required_optimizations(self):
      if self.bufs[0].dtype.__class__ is ImageDType:
          unit_stride_axes_mul_4 = [
              i
              for i in self.sts[0].unit_stride_axes(ignore_valid=True)
              if self.sts[0].shape[i] % 4 == 0
          ]
          assert (
              len(unit_stride_axes_mul_4) >= 1
          ), f"needs a unit stride axis in {self.bufs[0]}"
          if (
              len(unit_stride_axes_mul_4)
              and all(
                  x < (self.shape_len - self.upcasted)
                  for x in unit_stride_axes_mul_4
              )
              and unit_stride_axes_mul_4[0]
              not in self.upcast_in_mid_reduce_axes
          ):  # noqa: E501
              self.apply_opt(
                  Opt(OptOps.UPCAST, unit_stride_axes_mul_4[0], 4)
              )
  
imports: from __future__ import annotations
  import os, math, itertools
  from typing import NamedTuple, Optional, List, Tuple, cast, Dict, Union
  from tinygrad.ops import LazyOp, FlopCounter, get_lazyop_info, UnaryOps, BinaryOps, ReduceOps, MemBuffer, ConstBuffer, BufferOps
  from tinygrad.device import Device, Compiled
  from tinygrad.dtype import dtypes, ImageDType, DType
  from tinygrad.helpers import dedup, colored, ansilen, getenv, prod, DEBUG, round_up, all_int
  from tinygrad.shape.shapetracker import ShapeTracker, get_contraction
  from tinygrad.shape.symbolic import sint
  from tinygrad.shape.view import View, strides_for_shape
  from dataclasses import dataclass
  from enum import Enum, auto
label_desc: Use image node_id 28 for calling the Kernel obj's underlying member method code with example usage: obj.required_optimizations() without return types