code: def test_numpy_serializer():
      seed_everything(42)
  
      serializer_tensor = NumpySerializer()
  
      shapes = [
          (10,),
          (10, 10),
          (10, 10, 10),
          (10, 10, 10, 5),
          (10, 10, 10, 5, 4),
      ]
      for dtype in _NUMPY_DTYPES_MAPPING.values():
          # Those types aren't supported
          if dtype.name in ["object", "bytes", "str", "void"]:
              continue
          for shape in shapes:
              tensor = np.ones(shape, dtype=dtype)
              data, _ = serializer_tensor.serialize(tensor)
              deserialized_tensor = serializer_tensor.deserialize(data)
              assert deserialized_tensor.dtype == dtype
              np.testing.assert_equal(tensor, deserialized_tensor)
  
file_path: pytorch-lightning/tests/tests_data/streaming/test_serializer.py
imports: import os
  import sys
  from time import time
  import numpy
  import pytest
  import torch
  from lightning import seed_everything
  from lightning.data.streaming.serializers import _AV_AVAILABLE, _NUMPY_DTYPES_MAPPING, _SERIALIZERS, _TORCH_DTYPES_MAPPING, _TORCH_VISION_AVAILABLE, IntSerializer, NoHeaderNumpySerializer, NoHeaderTensorSerializer, NumpySerializer, PickleSerializer, PILSerializer, TensorSerializer, VideoSerializer
  from lightning_utilities.core.imports import RequirementCache
label_desc: Use image node_id 5 for calling a global function with example usage: test_numpy_serializer() without return types