






'''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

a__       =     TypeVar("""T""")


class    _lowerCAmelCase			(		Generic[T]      ):



				"""simple docstring"""



				def __init__(      self    :    Any			,		UpperCamelCase__    :    bool = True):






											'''simple docstring'''







											snake_case__	  =       {}  # dictionary of lists
											snake_case__	  =       directed



				def 					__magic_name__							(      self    :    Optional[Any]			,		UpperCamelCase__    :    T			,		UpperCamelCase__    :    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(UpperCamelCase__)
																									self.adj_list[destination_vertex].append(UpperCamelCase__)
																		# 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(UpperCamelCase__)
																									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(UpperCamelCase__)
																									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:
																									snake_case__	  =       [destination_vertex]
																									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(UpperCamelCase__)
																		# 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(UpperCamelCase__)
																									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:
																									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:
																									snake_case__	  =       [destination_vertex]
																									snake_case__	  =       []

											return self



				def __repr__(      self    :    List[Any]):






											'''simple docstring'''







											return pformat(self.adj_list)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__       =     {
    """configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """LILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """LiltForQuestionAnswering""",
	    """LiltForSequenceClassification""",
	    """LiltForTokenClassification""",
	    """LiltModel""",
	    """LiltPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lilt import (
		    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LiltForQuestionAnswering,
		    LiltForSequenceClassification,
		    LiltForTokenClassification,
		    LiltModel,
		    LiltPreTrainedModel,
		)

else:
	import sys

	a__       =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
