code: def to_movement_ops(self) -> List[Tuple[MovementOps, Tuple]]:
      to_apply: List[Tuple[MovementOps, Tuple]] = []
      for v in self.views:
          real_shape = (
              tuple(y - x for x, y in v.mask) if v.mask else v.shape
          )
          real_offset = (
              0
              if 0 in real_shape
              else (
                  v.offset
                  + (
                      sum(
                          x * st
                          for (x, _), st in zip(v.mask, v.strides)
                      )
                      if v.mask
                      else 0
                  )
              )
          )
          # first, we apply the offset
          # then, we make it the correct shape
          # then, we apply permutations
          to_apply.append(
              (
                  MovementOps.AS_STRIDED,
                  (
                      tuple(
                          [
                              s if st != 0 else 1
                              for s, st in zip(real_shape, v.strides)
                          ]
                      ),
                      v.strides,
                      real_offset,
                  ),
              )
          )
          # then, we apply pre expand pads
          if v.mask is not None:
              pre_expand_pads = tuple(
                  (x, s - y) if st != 0 else (0, 0)
                  for (x, y), s, st in zip(v.mask, v.shape, v.strides)
              )
              post_expand_pads = tuple(
                  (x, s - y) if st == 0 else (0, 0)
                  for (x, y), s, st in zip(v.mask, v.shape, v.strides)
              )
              if any(x != (0, 0) for x in pre_expand_pads):
                  to_apply.append((MovementOps.PAD, pre_expand_pads))
                  real_shape = tuple(
                      x + s[0] + s[1]
                      for x, s in zip(real_shape, pre_expand_pads)
                  )
          # then, we do any expands
          # NOTE: this is a good idea even without masks, since torch doesn't support negative strides and has to make a copy
          if any(
              s != 1 and st == 0 for s, st in zip(real_shape, v.strides)
          ):
              to_apply.append((MovementOps.EXPAND, real_shape))
          # lastly, we apply post expand pads
          if v.mask is not None and any(
              x != (0, 0) for x in post_expand_pads
          ):
              to_apply.append((MovementOps.PAD, post_expand_pads))
      return to_apply
  
imports: from __future__ import annotations
  import functools, itertools, operator
  from dataclasses import dataclass
  from typing import Tuple, List, Optional, Dict, Set, cast, Union, Iterable
  from tinygrad.ops import MovementOps
  from tinygrad.helpers import prod, merge_dicts, getenv
  from tinygrad.shape.symbolic import Variable, MulNode, Node, SumNode, NumNode, sint
  from tinygrad.shape.view import View, _merge_dims
label_desc: Use image node_id 11 for calling the ShapeTracker obj's underlying member method code with example usage: obj.to_movement_ops() and returns: to_apply