code: def test_arrow_block_slice_copy():
      # Test that ArrowBlock slicing properly copies the underlying Arrow
      # table.
      def check_for_copy(table1, table2, a, b, is_copy):
          expected_slice = table1.slice(a, b - a)
          assert table2.equals(expected_slice)
          assert table2.schema == table1.schema
          assert table1.num_columns == table2.num_columns
          for col1, col2 in zip(table1.columns, table2.columns):
              assert col1.num_chunks == col2.num_chunks
              for chunk1, chunk2 in zip(col1.chunks, col2.chunks):
                  bufs1 = chunk1.buffers()
                  bufs2 = chunk2.buffers()
                  expected_offset = 0 if is_copy else a
                  assert chunk2.offset == expected_offset
                  assert len(chunk2) == b - a
                  if is_copy:
                      assert bufs2[1].address != bufs1[1].address
                  else:
                      assert bufs2[1].address == bufs1[1].address
  
      n = 20
      df = pd.DataFrame(
          {
              "one": list(range(n)),
              "two": ["a"] * n,
              "three": [np.nan] + [1.5] * (n - 1),
          }
      )
      table = pa.Table.from_pandas(df)
      a, b = 5, 10
      block_accessor = BlockAccessor.for_block(table)
  
      # Test with copy.
      table2 = block_accessor.slice(a, b, True)
      check_for_copy(table, table2, a, b, is_copy=True)
  
      # Test without copy.
      table2 = block_accessor.slice(a, b, False)
      check_for_copy(table, table2, a, b, is_copy=False)
  
imports: import os
  import numpy
  import pandas
  import pyarrow
  import pytest
  import ray
  from ray.data._internal.arrow_ops.transform_pyarrow import concat, unify_schemas
  from ray.data.block import BlockAccessor
  from ray.data.extensions import ArrowTensorArray, ArrowTensorType, ArrowVariableShapedTensorType
label_desc: Use image node_id 11 for calling a global function with example usage: test_arrow_block_slice_copy() without return types