"""simple docstring"""







from typing import List, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE	:		Dict   =   logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE	:		Tuple   =   {
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}






class      _SCREAMING_SNAKE_CASE							(			UpperCAmelCase				):



   '''simple docstring'''



   __UpperCAmelCase	:							Optional[int]    =    "led"
   __UpperCAmelCase	:							List[str]    =    {
       "num_attention_heads": "encoder_attention_heads",
       "hidden_size": "d_model",
       "attention_probs_dropout_prob": "attention_dropout",
       "initializer_range": "init_std",
   }







   def __init__(	self ,				_SCREAMING_SNAKE_CASE=50265 ,				_SCREAMING_SNAKE_CASE=16384 ,				_SCREAMING_SNAKE_CASE=1024 ,				_SCREAMING_SNAKE_CASE=12 ,				_SCREAMING_SNAKE_CASE=4096 ,				_SCREAMING_SNAKE_CASE=16 ,				_SCREAMING_SNAKE_CASE=12 ,				_SCREAMING_SNAKE_CASE=4096 ,				_SCREAMING_SNAKE_CASE=16 ,				_SCREAMING_SNAKE_CASE=0.0 ,				_SCREAMING_SNAKE_CASE=0.0 ,				_SCREAMING_SNAKE_CASE=True ,				_SCREAMING_SNAKE_CASE=True ,				_SCREAMING_SNAKE_CASE="gelu" ,				_SCREAMING_SNAKE_CASE=1024 ,				_SCREAMING_SNAKE_CASE=0.1 ,				_SCREAMING_SNAKE_CASE=0.0 ,				_SCREAMING_SNAKE_CASE=0.0 ,				_SCREAMING_SNAKE_CASE=0.02 ,				_SCREAMING_SNAKE_CASE=2 ,				_SCREAMING_SNAKE_CASE=0.0 ,				_SCREAMING_SNAKE_CASE=1 ,				_SCREAMING_SNAKE_CASE=0 ,				_SCREAMING_SNAKE_CASE=2 ,				_SCREAMING_SNAKE_CASE = 512 ,				**_SCREAMING_SNAKE_CASE ,				):


      '''simple docstring'''

      __lowerCamelCase    		=					vocab_size
      __lowerCamelCase    		=					max_encoder_position_embeddings
      __lowerCamelCase    		=					max_decoder_position_embeddings
      __lowerCamelCase    		=					d_model
      __lowerCamelCase    		=					encoder_ffn_dim
      __lowerCamelCase    		=					encoder_layers
      __lowerCamelCase    		=					encoder_attention_heads
      __lowerCamelCase    		=					decoder_ffn_dim
      __lowerCamelCase    		=					decoder_layers
      __lowerCamelCase    		=					decoder_attention_heads
      __lowerCamelCase    		=					dropout
      __lowerCamelCase    		=					attention_dropout
      __lowerCamelCase    		=					activation_dropout
      __lowerCamelCase    		=					activation_function
      __lowerCamelCase    		=					init_std
      __lowerCamelCase    		=					encoder_layerdrop
      __lowerCamelCase    		=					decoder_layerdrop
      __lowerCamelCase    		=					classifier_dropout
      __lowerCamelCase    		=					use_cache
      __lowerCamelCase    		=					encoder_layers
      __lowerCamelCase    		=					attention_window

      super().__init__(
          pad_token_id=_SCREAMING_SNAKE_CASE ,				bos_token_id=_SCREAMING_SNAKE_CASE ,				eos_token_id=_SCREAMING_SNAKE_CASE ,				is_encoder_decoder=_SCREAMING_SNAKE_CASE ,				decoder_start_token_id=_SCREAMING_SNAKE_CASE ,				**_SCREAMING_SNAKE_CASE ,				)












"""simple docstring"""

class 							lowercase   :







				def __init__(				self :       Union[str, Any]   ,  _lowerCamelCase :       int							):



					"""simple docstring"""

					A_	:					Optional[int]						 =		data
					A_	:					int
					A_	:					Node

def 		lowercase_   (		_UpperCAmelCase						):




	"""simple docstring"""






	A_	:					List[str]						 =		0
	A_	:					List[str]						 =		x

def 		lowercase_   (		_UpperCAmelCase	,   _UpperCAmelCase						):




	"""simple docstring"""






	A_ ,			A_	:					Any						 =		find_set(_UpperCAmelCase						), find_set(_UpperCAmelCase						)
	if x == y:
		return

	elif x.rank > y.rank:
		A_	:					Optional[int]						 =		x
	else:
		A_	:					Optional[int]						 =		y
		if x.rank == y.rank:
			y.rank += 1

def 		lowercase_   (		_UpperCAmelCase						):




	"""simple docstring"""






	if x != x.parent:
		A_	:					Union[str, Any]						 =		find_set(x.parent						)
	return x.parent

def 		lowercase_   (		_UpperCAmelCase						):




	"""simple docstring"""






	A_	:					str						 =		({0, 1, 2}, {3, 4, 5})
	for s in sets:
		if node.data in s:
			return s
	A_	:					Optional[int]						 =		f"""{node.data} is not in {sets}"""
	raise ValueError(_UpperCAmelCase						)

def 		lowercase_   (		):




	"""simple docstring"""






	A_	:					Dict						 =		[Node(_UpperCAmelCase						) for i in range(6						)]
	for v in vertex:
		make_set(_UpperCAmelCase						)

	union_set(vertex[0]	,   vertex[1]						)
	union_set(vertex[1]	,   vertex[2]						)
	union_set(vertex[3]	,   vertex[4]						)
	union_set(vertex[3]	,   vertex[5]						)

	for nodea in vertex:
		for nodea in vertex:
			if find_python_set(_UpperCAmelCase						).isdisjoint(find_python_set(_UpperCAmelCase						)						):
				assert find_set(_UpperCAmelCase						) != find_set(_UpperCAmelCase						)
			else:
				assert find_set(_UpperCAmelCase						) == find_set(_UpperCAmelCase						)


if __name__ == "__main__":
		test_disjoint_set()





