code: def test_float4_multidim_sometimes_unaligned(self):
      a = Tensor.rand(1, 1, 7).realize()
      b = (
          Tensor.rand(1, 1, 5)
          .realize()
          .shrink(((0, 1), (0, 1), (1, 5)))
      )
      c = a.conv2d(b)
      # the first conv dot product is aligned in a. If we upcast the output and reduce
      # dimension, then we could do float4 for only that one set of loads, but we currently
      # don't.
  
      s = c.lazydata.schedule()[0]
      k = Linearizer(s.ast)
      k.upcast()
      k.upcast()
      k.linearize()
  
      assert TestFloat4.count_float4(k) == (0, 1)
  
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 7 for calling the TestFloat4 obj's underlying member method code with example usage: obj.test_float4_multidim_sometimes_unaligned() without return types