code: def apply_opt(self, opt: Opt):
      assert not self.dont_use_locals or opt.op not in {
          OptOps.LOCAL,
          OptOps.LASTLOCAL,
          OptOps.GROUP,
          OptOps.GROUPTOP,
          OptOps.UPCASTMID,
      }, "not using locals"  # noqa: E501
      self.applied_opts.append(opt)
      if opt.axis is not None:
          axis = opt.axis + (
              self.first_reduce
              if opt.op == OptOps.UNROLL
              else (
                  self.first_reduce + len(self.group_for_reduce)
                  if opt.op in [OptOps.GROUP, OptOps.GROUPTOP]
                  else 0
              )
          )  # noqa: E501
      else:
          axis = -1
      if opt.amt is not None:
          amt = opt.amt if opt.amt != 0 else self.full_shape[axis]
          assert (
              isinstance(amt, int) and amt != 1
          ), "shift/padto of amt 1 or Node is meaningless"
          if opt.op != OptOps.PADTO:
              assert (
                  self.full_shape[axis] % amt == 0
              ), "no longer valid shift"
      else:
          amt = -1
      if opt.op in [OptOps.LOCAL, OptOps.LASTLOCAL]:  # cyan
          assert self.opts.has_local, "target does not support local"
          assert axis < self.first_reduce, "can't local a reduce"
          if opt.op == OptOps.LOCAL:
              assert (
                  not self.tensor_core
              ), "can't local with tensor cores"
              self.shift_to(axis, amt, insert_before=self.first_reduce)
          else:
              self.shift_to(
                  axis,
                  amt,
                  insert_before=self.first_reduce - self.local_dims,
              )
          self.local_dims += 1
      elif opt.op in [OptOps.GROUP, OptOps.GROUPTOP]:  # green
          assert (
              self.opts.has_local and self.opts.has_shared
          ), "target does not support local or shared mem"
          assert (
              axis >= self.first_reduce + len(self.group_for_reduce)
              and axis < self.shape_len - self.upcasted
          ), "must be reduce axis to group"
          assert not self.tensor_core, "can't group with tensor cores"
          self.shift_to(
              axis,
              amt,
              top=(opt.op == OptOps.GROUPTOP),
              insert_before=self.first_reduce
              + len(self.group_for_reduce),
          )
          self.group_for_reduce.append(amt)
      elif opt.op == OptOps.UNROLL:  # purple
          assert (
              axis < self.shape_len - self.upcasted
          ), "can't upcasted already upcasted"
          assert amt <= 32, "don't unroll more than 32"
          self.shift_to(axis, amt, insert_before=None)
          self.upcast()
      elif opt.op == OptOps.UPCAST:  # yellow
          assert axis < self.first_reduce, "upcast is for non-reduce"
          assert amt <= 8, "don't upcast more than 8"
          self.shift_to(axis, amt, insert_before=None)
          self.upcast()
      elif opt.op == OptOps.UPCASTMID:  # white
          assert (
              self.bufs[0].dtype.name.startswith("image")
              and not self.float4_axis(0)
              and self.group_for_reduce
              and self.first_reduce <= 2
              and prod(self.sts[0].shape) > 1
          ), "invalid upcast mid reduce"  # noqa: E501
          axes = self.sts[0].unit_stride_axes()
          assert (
              len(axes) == 1
          ), f"wrong number of stride 1 axis : {axes}"
          assert axes[0] == axis, "wrong axis"
          assert amt == 4, "don't upcast mid anything but 4"
          self.shift_to(
              axis,
              amt,
              insert_before=self.first_reduce
              + len(self.group_for_reduce),
          )
          self.group_for_reduce.append(amt)
      elif opt.op == OptOps.NOLOCALS:
          assert (
              self.opts.has_local and not self.dont_use_locals
          ), "NOLOCALS is meaningless if target does not support local or already not using locals"
          assert (
              self.local_dims == 0 and len(self.group_for_reduce) == 0
          ), "can't have no locals with locals"
          self.dont_use_locals = True
      elif opt.op == OptOps.PADTO:
          assert (
              not self.ast.vars()
          ), "does not work with symbolic shape"
          assert axis < self.first_reduce, "cannot pad a reduce axis"
          padded = False
          for i, st in enumerate(self.sts):
              assert (
                  self.sts[i].shape[axis] > amt // 2
              ), "pad adds more than double the work"
              if (
                  ru := round_up(self.sts[i].shape[axis], amt)
                  - self.sts[i].shape[axis]
              ):
                  # pad right seems to be faster
                  self.sts[i] = st.pad(
                      ((0, 0),) * axis
                      + ((0, ru),)
                      + ((0, 0),) * (len(st.shape) - axis - 1)
                  )
                  padded = True
          assert padded, "nothing was padded"
      return self.simplify_ones()
  
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 27 for calling the Kernel obj's underlying member method code with example usage: obj.apply_opt(opt) and returns: self