"""simple docstring"""






import sys
from collections.abc import Mapping

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter


class 					UpperCAmelCase		(TensorFormatter[Mapping, np.ndarray, Mapping]						):



    """simple docstring"""

    def __init__(     self					,    _UpperCAmelCase=None					,    **_UpperCAmelCase							):
       super().__init__(features=_UpperCAmelCase							)
       lowercase__:     Optional[Any]      =   np_array_kwargs






    def _snake_case    (     self					,    _UpperCAmelCase							):






       if isinstance(_UpperCAmelCase					,    _UpperCAmelCase							):
          if column and all(
              isinstance(_UpperCAmelCase					,    np.ndarray							) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column							):
             return np.stack(_UpperCAmelCase							)
          else:
             # don't use np.array(column, dtype=object)
             # since it fails in certain cases
             # see https://stackoverflow.com/q/51005699
             lowercase__:     Optional[Any]      =   np.empty(len(_UpperCAmelCase							)					,    dtype=_UpperCAmelCase							)
             lowercase__:     Optional[int]      =   column
             return out
       return column






    def _snake_case    (     self					,    _UpperCAmelCase							):






       if isinstance(_UpperCAmelCase					,    (str, bytes, type(_UpperCAmelCase							))							):
          return value
       elif isinstance(_UpperCAmelCase					,    (np.character, np.ndarray)							) and np.issubdtype(value.dtype					,    np.character							):
          return value
       elif isinstance(_UpperCAmelCase					,    np.number							):
          return value

       lowercase__:     List[Any]      =   {}

       if isinstance(_UpperCAmelCase					,    np.ndarray							) and np.issubdtype(value.dtype					,    np.integer							):
          lowercase__:     str      =   {'''dtype''': np.intaa}
       elif isinstance(_UpperCAmelCase					,    np.ndarray							) and np.issubdtype(value.dtype					,    np.floating							):
          lowercase__:     int      =   {'''dtype''': np.floataa}
       elif config.PIL_AVAILABLE and "PIL" in sys.modules:
          import PIL.Image

          if isinstance(_UpperCAmelCase					,    PIL.Image.Image							):
             return np.asarray(_UpperCAmelCase					,    **self.np_array_kwargs							)

       return np.asarray(_UpperCAmelCase					,    **{**default_dtype, **self.np_array_kwargs}							)






    def _snake_case    (     self					,    _UpperCAmelCase							):






       if config.TORCH_AVAILABLE and "torch" in sys.modules:
          import torch

          if isinstance(_UpperCAmelCase					,    torch.Tensor							):
             return self._tensorize(data_struct.detach().cpu().numpy()[()]							)
       if hasattr(_UpperCAmelCase					,    '''__array__'''							) and not isinstance(_UpperCAmelCase					,    (np.ndarray, np.character, np.number)							):
          lowercase__:     Tuple      =   data_struct.__array__()
       # support for nested types like struct of list of struct
       if isinstance(_UpperCAmelCase					,    np.ndarray							):
          if data_struct.dtype == object:
             return self._consolidate([self.recursive_tensorize(_UpperCAmelCase							) for substruct in data_struct]							)
       if isinstance(_UpperCAmelCase					,    (list, tuple)							):
          return self._consolidate([self.recursive_tensorize(_UpperCAmelCase							) for substruct in data_struct]							)
       return self._tensorize(_UpperCAmelCase							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       return map_nested(self._recursive_tensorize					,    _UpperCAmelCase					,    map_list=_UpperCAmelCase							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       lowercase__:     Union[str, Any]      =   self.numpy_arrow_extractor().extract_row(_UpperCAmelCase							)
       lowercase__:     Optional[Any]      =   self.python_features_decoder.decode_row(_UpperCAmelCase							)
       return self.recursive_tensorize(_UpperCAmelCase							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       lowercase__:     Optional[int]      =   self.numpy_arrow_extractor().extract_column(_UpperCAmelCase							)
       lowercase__:     Optional[int]      =   self.python_features_decoder.decode_column(_UpperCAmelCase					,    pa_table.column_names[0]							)
       lowercase__:     Optional[int]      =   self.recursive_tensorize(_UpperCAmelCase							)
       lowercase__:     str      =   self._consolidate(_UpperCAmelCase							)
       return column






    def _snake_case    (     self					,    _UpperCAmelCase							):
       lowercase__:     Any      =   self.numpy_arrow_extractor().extract_batch(_UpperCAmelCase							)
       lowercase__:     Optional[Any]      =   self.python_features_decoder.decode_batch(_UpperCAmelCase							)
       lowercase__:     Optional[int]      =   self.recursive_tensorize(_UpperCAmelCase							)
       for column_name in batch:
          lowercase__:     Any      =   self._consolidate(batch[column_name]							)
       return batch

"""simple docstring"""






class 					UpperCAmelCase		:



    """simple docstring"""

    def __init__(     self					,    _UpperCAmelCase=None							):
       lowercase__:     Optional[int]      =   data
       lowercase__:     Dict      =   None






    def __repr__(     self							):
       lowercase__:     int      =   ''''''
       lowercase__:     Any      =   self
       while temp:
          string_rep += F"""<{temp.data}> ---> """
          lowercase__:     Any      =   temp.next
       string_rep += "<END>"
       return string_rep



def SCREAMING_SNAKE_CASE__    (     __UpperCAmelCase				)						->						str:

   # if elements_list is empty
   if not elements_list:
      raise Exception('''The Elements List is empty'''				)

   # Set first element as Head
   lowercase__:     Union[str, Any]      =   Node(elements_list[0]				)
   lowercase__:     List[str]      =   head
   # Loop through elements from position 1
   for data in elements_list[1:]:
      lowercase__:     Tuple      =   Node(__UpperCAmelCase				)
      lowercase__:     Tuple      =   current.next
   return head


__A         =				[1, 3, 5, 3_2, 4_4, 1_2, 4_3]
print(f'''List: {list_data}''')
print("Creating Linked List from List.")
__A         =				make_linked_list(list_data)
print("Linked List:")




print(linked_list)
