code: def test_masked_upcast_wino_full(self):
      old_wino = Tensor.wino
      Tensor.wino = True
      x, w = (
          Tensor.rand(1, 4, 9, 9, requires_grad=True).realize(),
          Tensor.rand(4, 4, 3, 3, requires_grad=True).realize(),
      )
      out = Tensor.conv2d(x, w, padding=1)
      upcasts = []
      # collect upcasts of tile transform kernels
      for i, si in enumerate(out.lazydata.schedule()):
          k = Linearizer(si.ast)
          k.hand_coded_optimizations()
          if k.reduceop is not None:
              continue  # not a tile transform kernel (there is a gemm reduce kernel)
          if len(k.bufs) < 100:
              continue  # not a tile transform kernel (there's a permute kernel at the end)
          upcasts.append(
              tuple(
                  k.full_shape[k.shape_len - k.upcasted : k.shape_len]
              )
          )
      assert len(upcasts) == 3  # 3 transformation matrices
      # TODO: what did this fix?
      assert (
          upcasts.count((6, 6)) == 2
      )  # and upcasts.count((4, 4)) == 1
  
      out.mean().backward()
      for si in x.grad.lazydata.schedule() + w.grad.lazydata.schedule():
          k = Linearizer(si.ast)
          k.hand_coded_optimizations()
          k.linearize()
          if len(k.bufs) < 20:
              continue  # not a tile transform kernel
          # heuristic number to make sure that at least some upcasts but not too many upcasts are being done
          assert (
              6
              <= prod(
                  k.full_shape[k.shape_len - k.upcasted : k.shape_len]
              )
              <= 49
          )
  
      Tensor.wino = old_wino
  
imports: import numpy
  import unittest, os
  from tinygrad.codegen.kernel import Opt, OptOps, tensor_cores
  from tinygrad.codegen.linearizer import Linearizer, UOp, UOps, expand_node
  from tinygrad.device import Compiled, Device, Buffer
  from tinygrad.ops import BufferOps, MemBuffer, ConstBuffer, LazyOp, LoadOps, TernaryOps
  from tinygrad.shape.shapetracker import ShapeTracker
  from tinygrad.shape.view import View
  from tinygrad.shape.symbolic import MulNode, SumNode, Variable, NumNode, Node, create_rednode
  from tinygrad.tensor import Tensor
  from tinygrad.jit import CacheCollector
  from tinygrad.realize import run_schedule
  from tinygrad.helpers import prod
  from tinygrad.dtype import dtypes
label_desc: Use image node_id 3 for calling the TestHandCodedOpts obj's underlying member method code with example usage: obj.test_masked_upcast_wino_full() without return types