



"""simple docstring"""
from typing import List

import numpy as np

def    _snake_case		(		UpperCamelCase		:	dict		):
 UpperCAmelCase			:      Dict			=			{key: len(UpperCamelCase		) for key, value in gen_kwargs.items() if isinstance(UpperCamelCase    ,	UpperCamelCase		)}
 if len(set(lists_lengths.values()		)		) > 1:
  raise RuntimeError(
      (
          """Sharding is ambiguous for this dataset: """
          + """we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n"""
          + """\n""".join(F"\t- key {key} has length {length}" for key, length in lists_lengths.items()		)
          + """\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, """
          + """and use tuples otherwise. In the end there should only be one single list, or several lists with the same length."""
      )		)
 UpperCAmelCase			:      str			=			max(lists_lengths.values()    ,	default=0		)
 return max(1    ,	UpperCamelCase		)

def    _snake_case		(		UpperCamelCase		:	int    ,	UpperCamelCase		:	int		):
 UpperCAmelCase			:      Optional[int]			=			[]
 for group_idx in range(UpperCamelCase		):
  UpperCAmelCase			:      Tuple			=			num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
  if num_shards_to_add == 0:
   break
  UpperCAmelCase			:      Tuple			=			shards_indices_per_group[-1].stop if shards_indices_per_group else 0
  UpperCAmelCase			:      List[str]			=			range(UpperCamelCase    ,	start + num_shards_to_add		)
  shards_indices_per_group.append(UpperCamelCase		)
 return shards_indices_per_group

def    _snake_case		(		UpperCamelCase		:	dict    ,	UpperCamelCase		:	int		):
 UpperCAmelCase			:      Tuple			=			_number_of_shards_in_gen_kwargs(UpperCamelCase		)
 if num_shards == 1:
  return [dict(UpperCamelCase		)]
 else:
  UpperCAmelCase			:      Union[str, Any]			=			_distribute_shards(num_shards=UpperCamelCase    ,	max_num_jobs=UpperCamelCase		)
  return [
      {
          key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
          if isinstance(UpperCamelCase    ,	UpperCamelCase		)
          else value
          for key, value in gen_kwargs.items()
      }
      for group_idx in range(len(UpperCamelCase		)		)
  ]

def    _snake_case		(		UpperCamelCase		:	List[dict]		):
 return {
     key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
     if isinstance(gen_kwargs_list[0][key]    ,	UpperCamelCase		)
     else gen_kwargs_list[0][key]
     for key in gen_kwargs_list[0]
 }

def    _snake_case		(		UpperCamelCase		:	np.random.Generator    ,	UpperCamelCase		:	dict		):
 UpperCAmelCase			:      str			=			{len(UpperCamelCase		) for value in gen_kwargs.values() if isinstance(UpperCamelCase    ,	UpperCamelCase		)}
 UpperCAmelCase			:      Any			=			{}
 for size in list_sizes:
  UpperCAmelCase			:      Union[str, Any]			=			list(range(UpperCamelCase		)		)
  rng.shuffle(indices_per_size[size]		)
 # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
 UpperCAmelCase			:      Optional[Any]			=			dict(UpperCamelCase		)
 for key, value in shuffled_kwargs.items():
  if isinstance(UpperCamelCase    ,	UpperCamelCase		):
   UpperCAmelCase			:      Any			=			[value[i] for i in indices_per_size[len(UpperCamelCase		)]]
 return shuffled_kwargs





"""simple docstring"""
from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

A:     List[Any]										=	(3, 9, -1_1, 0, 7, 5, 1, -1)
A:     Union[str, Any]										=	(4, 6, 2, 0, 8, 1_0, 3, -2)



@dataclass
class    SCREAMING_SNAKE_CASE__						:
   __lowerCAmelCase						:     int
   __lowerCAmelCase						:     Node | None



class    SCREAMING_SNAKE_CASE__						:

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    UpperCAmelCase			:      Node | None			=			None
    for i in sorted(_SCREAMING_SNAKE_CASE   ,  reverse=_SCREAMING_SNAKE_CASE		):
     UpperCAmelCase			:      Union[str, Any]			=			Node(_SCREAMING_SNAKE_CASE   ,  self.head		)

   def __iter__(     self		)						->   Iterator[int]:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[Any]			=			self.head
    while node:
     yield node.data
     UpperCAmelCase			:      List[str]			=			node.next_node

   def __len__(     self		)						->   int:





    '''simple docstring'''




    return sum(1 for _ in self		)




   def __str__(     self		)						->   str:





    '''simple docstring'''




    return " -> ".join([str(_SCREAMING_SNAKE_CASE		) for node in self]		)

def    _snake_case		(		UpperCamelCase		:	SortedLinkedList    ,	UpperCamelCase		:	SortedLinkedList		):
 return SortedLinkedList(list(UpperCamelCase		) + list(UpperCamelCase		)		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      A:     Dict										=	SortedLinkedList
      print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))
