



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_lowercase     							=						{
    '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
    '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/config.json''',
    '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/config.json''',
    '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json''',
    '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/config.json''',
    '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/config.json''',
    '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/config.json''',
    '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json''',
}
class 				__A					( A_      ):
			UpperCamelCase					:Tuple     =			'''albert'''





			def __init__(self							,    __magic_name__=30000							,    __magic_name__=128							,    __magic_name__=4096							,    __magic_name__=12							,    __magic_name__=1							,    __magic_name__=64							,    __magic_name__=16384							,    __magic_name__=1							,    __magic_name__="gelu_new"							,    __magic_name__=0							,    __magic_name__=0							,    __magic_name__=512							,    __magic_name__=2							,    __magic_name__=0.02							,    __magic_name__=1E-12							,    __magic_name__=0.1							,    __magic_name__="absolute"							,    __magic_name__=0							,    __magic_name__=2							,    __magic_name__=3							,    **__magic_name__							,    ):
						super().__init__(pad_token_id=__magic_name__							,    bos_token_id=__magic_name__							,    eos_token_id=__magic_name__							,    **__magic_name__				)

						lowerCamelCase__ :      Optional[Any]								=		vocab_size
						lowerCamelCase__ :      Optional[int]								=		embedding_size
						lowerCamelCase__ :      Dict								=		hidden_size
						lowerCamelCase__ :      Union[str, Any]								=		num_hidden_layers
						lowerCamelCase__ :      Union[str, Any]								=		num_hidden_groups
						lowerCamelCase__ :      Optional[Any]								=		num_attention_heads
						lowerCamelCase__ :      int								=		inner_group_num
						lowerCamelCase__ :      int								=		hidden_act
						lowerCamelCase__ :      Optional[int]								=		intermediate_size
						lowerCamelCase__ :      Optional[Any]								=		hidden_dropout_prob
						lowerCamelCase__ :      Union[str, Any]								=		attention_probs_dropout_prob
						lowerCamelCase__ :      Dict								=		max_position_embeddings
						lowerCamelCase__ :      Union[str, Any]								=		type_vocab_size
						lowerCamelCase__ :      str								=		initializer_range
						lowerCamelCase__ :      Union[str, Any]								=		layer_norm_eps
						lowerCamelCase__ :      Tuple								=		classifier_dropout_prob
						lowerCamelCase__ :      str								=		position_embedding_type







class 				__A					( A_      ):





			@property
			def        _snake_case    (self				):
						if self.task == "multiple-choice":
									lowerCamelCase__ :      Tuple								=		{0: """batch""", 1: """choice""", 2: """sequence"""}
						else:
									lowerCamelCase__ :      List[Any]								=		{0: """batch""", 1: """sequence"""}
						return OrderedDict(
						    [
						        ("""input_ids""", dynamic_axis),
						        ("""attention_mask""", dynamic_axis),
						        ("""token_type_ids""", dynamic_axis),
						    ]				)








# 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

_lowercase     							=						TypeVar('''T''')
class 				__A					( Generic[T]      ):





			def __init__(self							,    __magic_name__ = True				):
						lowerCamelCase__ :      dict[T, list[T]]								=		{}  # dictionary of lists
						lowerCamelCase__ :      List[str]								=		directed





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__				):

						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__				)
												lowerCamelCase__ :      int								=		[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__				)
												lowerCamelCase__ :      Dict								=		[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:
												lowerCamelCase__ :      Any								=		[destination_vertex]
												lowerCamelCase__ :      Optional[Any]								=		[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__				)
												lowerCamelCase__ :      Optional[Any]								=		[]
									# 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:
												lowerCamelCase__ :      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:
												lowerCamelCase__ :      Optional[int]								=		[destination_vertex]
												lowerCamelCase__ :      List[Any]								=		[]

						return self





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



