code: def test_dynamically_defined_class(self):
      def fn():
          def create_class(multiplier: int):
              class DynamicFn(torch.autograd.Function):
                  @staticmethod
                  def forward(ctx, x):
                      return x * multiplier
  
                  @staticmethod
                  def backward(ctx, gO):
                      return gO * multiplier
  
              return DynamicFn
  
          for multiplier in [10, 20, 30]:
              x = torch.arange(0.0, 10, requires_grad=True)
              out = create_class(multiplier).apply(x)
              loss = out.sum()
              loss.backward()
              yield x.grad
  
      self.check_output_and_recompiles(fn, 3)
  
imports: import functools
  import re
  import sys
  import unittest
  from importlib.machinery import SourceFileLoader
  from pathlib import Path
  from unittest import mock
  import torch
  import torch.nn
  from torch import _inductor
  from torch._dynamo import compiled_autograd
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import counters
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
label_desc: Use image node_id 25 for calling the TestCompiledAutograd obj's underlying member method code with example usage: obj.test_dynamically_defined_class() and returns: DynamicFn, unknown, unknown