code: def numpy_to_block(
      batch: Union[np.ndarray, Dict[str, np.ndarray], Dict[str, list]],
  ) -> "pyarrow.Table":
      import pyarrow as pa
  
      from ray.data.extensions.tensor_extension import ArrowTensorArray
  
      if isinstance(batch, np.ndarray):
          batch = {TENSOR_COLUMN_NAME: batch}
      elif not isinstance(batch, collections.abc.Mapping) or any(
          not is_valid_udf_return(col) for col in batch.values()
      ):
          raise ValueError(
              "Batch must be an ndarray or dictionary of ndarrays when converting "
              f"a numpy batch to a block, got: {type(batch)} "
              f"({_truncated_repr(batch)})"
          )
      new_batch = {}
      for col_name, col in batch.items():
          # Coerce to np.ndarray format if possible.
          col = convert_udf_returns_to_numpy(col)
          # Use Arrow's native *List types for 1-dimensional ndarrays.
          if col.dtype.type is np.object_ or col.ndim > 1:
              col = ArrowTensorArray.from_numpy(col)
          new_batch[col_name] = col
      return pa.Table.from_pydict(new_batch)
  
imports: import collections
  import heapq
  import random
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterator, List, Optional, Tuple, TypeVar, Union
  import numpy
  from ray._private.utils import _get_pyarrow_version
  from ray.air.constants import TENSOR_COLUMN_NAME
  from ray.data._internal.arrow_ops import transform_polars, transform_pyarrow
  from ray.data._internal.numpy_support import convert_udf_returns_to_numpy, is_valid_udf_return
  from ray.data._internal.table_block import TableBlockAccessor, TableBlockBuilder
  from ray.data._internal.util import _truncated_repr, find_partitions
  from ray.data.block import Block, BlockAccessor, BlockExecStats, BlockMetadata, KeyType, U
  from ray.data.context import DataContext
  from ray.data.row import TableRow
label_desc: Use image node_id 5 for calling the ArrowBlockAccessor obj's underlying member method code with example usage: obj.numpy_to_block(batch) and returns: pa