code: def test_dynamic(self) -> None:
      class DynamicShapeSimpleModel(torch.nn.Module):
          def __init__(self):
              super().__init__()
  
          def forward(self, a, b, c) -> torch.Tensor:
              d = (torch.matmul(a, b) + c) / 2
              d_s0 = d.shape[0]
              d_s1 = d.shape[1]
              d_s3 = d_s0 * d_s1
              e = d.view(d_s3)
              return torch.cat([e, e])
  
      inputs = (torch.randn(2, 4), torch.randn(4, 7), torch.randn(2, 7))
      dim0_ac = torch.export.Dim("dim0_ac")
      dynamic_shapes = {"a": {0: dim0_ac}, "b": None, "c": {0: dim0_ac}}
      self.check_graph(
          DynamicShapeSimpleModel(), inputs, dynamic_shapes
      )
  
imports: import io
  import pathlib
  import tempfile
  import unittest
  import zipfile
  import torch
  import torch._dynamo
  from torch.export import export, save, load, Dim
  from torch._export.db.case import ExportCase, normalize_inputs, SupportLevel
  from torch._export.db.examples import all_examples
  from torch._export.serde.serialize import ExportedProgramDeserializer, ExportedProgramSerializer, canonicalize, deserialize, serialize, SerializeError
  from torch._subclasses.fake_tensor import FakeTensor
  from torch.fx.experimental.symbolic_shapes import is_concrete_int
  import torch.utils._pytree
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TestCase, TemporaryFileName, IS_FBCODE, IS_MACOS, IS_SANDCASTLE, IS_WINDOWS, find_library_location
label_desc: Use image node_id 4 for calling the TestDeserialize obj's underlying member method code with example usage: obj.test_dynamic() and returns: torch