code: def test_exported_program_torch_distributions_normal_Normal(self):
      class Model(torch.nn.Module):
          def __init__(self):
              self.normal = torch.distributions.normal.Normal(0, 1)
              super().__init__()
  
          def forward(self, x):
              return self.normal.sample(x.shape)
  
      x = torch.randn(2, 3)
      with torch.no_grad():
          exported_program = torch.export.export(Model(), args=(x,))
          _ = torch.onnx.dynamo_export(
              exported_program,
              x,
          )
  
imports: from __future__ import annotations
  import io
  import tempfile
  from typing import Mapping, Tuple
  import onnx
  import pytorch_test_common
  import torch
  import transformers
  from torch import nn
  from torch._subclasses import fake_tensor
  from torch.nn import functional
  from torch.onnx import dynamo_export, ExportOptions
  from torch.onnx._internal.diagnostics import infra
  from torch.onnx._internal.fx import diagnostics, registration
  from torch.testing._internal import common_utils
label_desc: Use image node_id 25 for calling the TestFxToOnnx obj's underlying member method code with example usage: obj.test_exported_program_torch_distributions_normal_Normal() and returns: self