


# 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				      =   TypeVar("T")




class    UpperCAmelCase					(       Generic[T]    ):




			def __init__(						self							:		Union[str, Any]       ,       __magic_name__							:		bool = True						):







						"""simple docstring"""







						UpperCamelCase         =					{}  # dictionary of lists
						UpperCamelCase         =					directed




			def   lowerCamelCase_					(						self							:		str       ,       __magic_name__							:		T       ,       __magic_name__							:		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(__magic_name__						)
												self.adj_list[destination_vertex].append(__magic_name__						)
									# 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(__magic_name__						)
												UpperCamelCase         =					[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(__magic_name__						)
												UpperCamelCase         =					[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:
												UpperCamelCase         =					[destination_vertex]
												UpperCamelCase         =					[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(__magic_name__						)
									# 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(__magic_name__						)
												UpperCamelCase         =					[]
									# 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:
												UpperCamelCase         =					[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:
												UpperCamelCase         =					[destination_vertex]
												UpperCamelCase         =					[]

						return self





			def __repr__(						self							:		Any						):







						"""simple docstring"""







						return pformat(self.adj_list						)








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


__snake_case            =   logging.get_logger(__name__)

__snake_case            =   {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}




class    UpperCAmelCase					(       __snake_case    ):
			lowercase						= """lilt"""




			def __init__(						self							:		Tuple       ,       __magic_name__							:		Tuple=3_0_5_2_2       ,       __magic_name__							:		List[str]=7_6_8       ,       __magic_name__							:		Optional[Any]=1_2       ,       __magic_name__							:		str=1_2       ,       __magic_name__							:		Tuple=3_0_7_2       ,       __magic_name__							:		List[Any]="gelu"       ,       __magic_name__							:		Dict=0.1       ,       __magic_name__							:		str=0.1       ,       __magic_name__							:		Dict=5_1_2       ,       __magic_name__							:		Any=2       ,       __magic_name__							:		Optional[int]=0.02       ,       __magic_name__							:		Optional[int]=1e-12       ,       __magic_name__							:		Optional[int]=0       ,       __magic_name__							:		List[str]="absolute"       ,       __magic_name__							:		List[Any]=None       ,       __magic_name__							:		str=4       ,       __magic_name__							:		Any=1_0_2_4       ,       **__magic_name__							:		List[str]       ,       ):







						"""simple docstring"""







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

						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




