


# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

snake_case_						:			List[Any]													=							TypeVar('''T''')

class 						A__							(		Generic[T]  ):




						def __init__(       self					:      Tuple				,    _a					:      bool = True  )							->     None:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  ={}  # dictionary of lists
										_SCREAMING_SNAKE_CASE			  =directed




						def 							__UpperCamelCase				(       self					:      Union[str, Any]				,    _a					:      T				,    _a					:      T  )							->     GraphAdjacencyList[T]:


										"""simple docstring"""





										if not self.directed:  # For undirected graphs
														# if both source vertex and destination vertex are both present in the
														# adjacency list, add destination vertex to source vertex list of adjacent
														# vertices and add source vertex to destination vertex list of adjacent
														# vertices.
														if source_vertex in self.adj_list and destination_vertex in self.adj_list:
																		self.adj_list[source_vertex].append(_a  )
																		self.adj_list[destination_vertex].append(_a  )
														# if only source vertex is present in adjacency list, add destination vertex
														# to source vertex list of adjacent vertices, then create a new vertex with
														# destination vertex as key and assign a list containing the source vertex
														# as it's first adjacent vertex.
														elif source_vertex in self.adj_list:
																		self.adj_list[source_vertex].append(_a  )
																		_SCREAMING_SNAKE_CASE			  =[source_vertex]
														# if only destination vertex is present in adjacency list, add source vertex
														# to destination vertex list of adjacent vertices, then create a new vertex
														# with source vertex as key and assign a list containing the source vertex
														# as it's first adjacent vertex.
														elif destination_vertex in self.adj_list:
																		self.adj_list[destination_vertex].append(_a  )
																		_SCREAMING_SNAKE_CASE			  =[destination_vertex]
														# if both source vertex and destination vertex are not present in adjacency
														# list, create a new vertex with source vertex as key and assign a list
														# containing the destination vertex as it's first adjacent vertex also
														# create a new vertex with destination vertex as key and assign a list
														# containing the source vertex as it's first adjacent vertex.
														else:
																		_SCREAMING_SNAKE_CASE			  =[destination_vertex]
																		_SCREAMING_SNAKE_CASE			  =[source_vertex]
										else:  # For directed graphs
														# if both source vertex and destination vertex are present in adjacency
														# list, add destination vertex to source vertex list of adjacent vertices.
														if source_vertex in self.adj_list and destination_vertex in self.adj_list:
																		self.adj_list[source_vertex].append(_a  )
														# if only source vertex is present in adjacency list, add destination
														# vertex to source vertex list of adjacent vertices and create a new vertex
														# with destination vertex as key, which has no adjacent vertex
														elif source_vertex in self.adj_list:
																		self.adj_list[source_vertex].append(_a  )
																		_SCREAMING_SNAKE_CASE			  =[]
														# if only destination vertex is present in adjacency list, create a new
														# vertex with source vertex as key and assign a list containing destination
														# vertex as first adjacent vertex
														elif destination_vertex in self.adj_list:
																		_SCREAMING_SNAKE_CASE			  =[destination_vertex]
														# if both source vertex and destination vertex are not present in adjacency
														# list, create a new vertex with source vertex as key and a list containing
														# destination vertex as it's first adjacent vertex. Then create a new vertex
														# with destination vertex as key, which has no adjacent vertex
														else:
																		_SCREAMING_SNAKE_CASE			  =[destination_vertex]
																		_SCREAMING_SNAKE_CASE			  =[]

										return self




						def __repr__(       self					:      Optional[Any]  )							->     str:


										"""simple docstring"""





										return pformat(self.adj_list  )



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


snake_case_						:			int													=							logging.get_logger(__name__)

snake_case_						:			Optional[Any]													=							{
    '''SCUT-DLVCLab/lilt-roberta-en-base''': (
        '''https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'''
    ),
}

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						"lilt"




						def __init__(       self					:      int				,    _a					:      Dict=3_0522				,    _a					:      str=768				,    _a					:      Optional[int]=12				,    _a					:      str=12				,    _a					:      List[str]=3072				,    _a					:      Any="gelu"				,    _a					:      int=0.1				,    _a					:      Any=0.1				,    _a					:      Union[str, Any]=512				,    _a					:      str=2				,    _a					:      List[Any]=0.02				,    _a					:      str=1E-12				,    _a					:      str=0				,    _a					:      str="absolute"				,    _a					:      Any=None				,    _a					:      Dict=4				,    _a					:      int=1024				,    **_a					:      List[Any]				,    )							->     Any:


										"""simple docstring"""





										super().__init__(pad_token_id=_a				,    **_a  )

										_SCREAMING_SNAKE_CASE			  =vocab_size
										_SCREAMING_SNAKE_CASE			  =hidden_size
										_SCREAMING_SNAKE_CASE			  =num_hidden_layers
										_SCREAMING_SNAKE_CASE			  =num_attention_heads
										_SCREAMING_SNAKE_CASE			  =hidden_act
										_SCREAMING_SNAKE_CASE			  =intermediate_size
										_SCREAMING_SNAKE_CASE			  =hidden_dropout_prob
										_SCREAMING_SNAKE_CASE			  =attention_probs_dropout_prob
										_SCREAMING_SNAKE_CASE			  =max_position_embeddings
										_SCREAMING_SNAKE_CASE			  =type_vocab_size
										_SCREAMING_SNAKE_CASE			  =initializer_range
										_SCREAMING_SNAKE_CASE			  =layer_norm_eps
										_SCREAMING_SNAKE_CASE			  =position_embedding_type
										_SCREAMING_SNAKE_CASE			  =classifier_dropout
										_SCREAMING_SNAKE_CASE			  =channel_shrink_ratio
										_SCREAMING_SNAKE_CASE			  =max_ad_position_embeddings