


'''simple docstring'''







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


a__  :					Any        =       logging.get_logger(__name__)

a__  :					str        =       {
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}
class 					lowercase_     (    a__   ):
    __UpperCAmelCase   			=	'lilt'


    def __init__(     self  ,					a=3_05_22  ,					a=7_68  ,					a=12  ,					a=12  ,					a=30_72  ,					a="gelu"  ,					a=0.1  ,					a=0.1  ,					a=5_12  ,					a=2  ,					a=0.02  ,					a=1e-12  ,					a=0  ,					a="absolute"  ,					a=None  ,					a=4  ,					a=10_24  ,					**a  ,					):
          super().__init__(pad_token_id=a  ,					**a    )

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










'''simple docstring'''




# 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

lowerCamelCase							:str				    =					TypeVar('''T''')







class 	_lowerCAmelCase							(			Generic[T] ):


	def __init__(self       ,      lowercase = True							):
				A_	:						dict[T, list[T]]	=     {}  # dictionary of lists
				A_	:						Any	=     directed


	def     _a	(self       ,      lowercase       ,      lowercase							):

				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(lowercase							)
										self.adj_list[destination_vertex].append(lowercase							)
							# 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(lowercase							)
										A_	:						Dict	=     [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(lowercase							)
										A_	:						int	=     [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:
										A_	:						Optional[Any]	=     [destination_vertex]
										A_	:						Tuple	=     [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(lowercase							)
							# 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(lowercase							)
										A_	:						Tuple	=     []
							# 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:
										A_	:						Tuple	=     [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:
										A_	:						int	=     [destination_vertex]
										A_	:						List[str]	=     []

				return self


	def __repr__(self							):
				return pformat(self.adj_list							)