code: def test_tensors_in_tables_from_pandas(ray_start_regular_shared):
      outer_dim = 3
      inner_shape = (2, 2, 2)
      shape = (outer_dim,) + inner_shape
      num_items = np.prod(np.array(shape))
      arr = np.arange(num_items).reshape(shape)
      df = pd.DataFrame(
          {"one": list(range(outer_dim)), "two": list(arr)}
      )
      # Cast column to tensor extension dtype.
      df["two"] = df["two"].astype(TensorDtype(shape, np.int64))
      ds = ray.data.from_pandas([df])
      values = [[s["one"], s["two"]] for s in ds.take()]
      expected = list(zip(list(range(outer_dim)), arr))
      for v, e in zip(sorted(values), expected):
          np.testing.assert_equal(v, e)
  
imports: import time
  import numpy
  import pandas
  import pyarrow
  import pytest
  import ray
  from ray.air.util.tensor_extensions.utils import _create_possibly_ragged_ndarray
  from ray.data.block import BlockAccessor
  from ray.data.extensions.tensor_extension import ArrowTensorArray, ArrowTensorType, ArrowVariableShapedTensorArray, ArrowVariableShapedTensorType, TensorArray, TensorDtype
  from ray.data.tests.conftest import *
  from ray.data.tests.util import extract_values
  from ray.tests.conftest import *
label_desc: Use image node_id 9 for calling a global function with example usage: test_tensors_in_tables_from_pandas(ray_start_regular_shared) without return types