


# 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      :    int		=					TypeVar("T")







class 			_lowercase (							Generic[T]):


       """simple docstring"""




       def __init__(   self							:			Dict					,      __lowerCamelCase							:			bool = True       ):


             '''simple docstring'''



             lowerCamelCase__		:				dict[T, list[T]]    =  {}  # dictionary of lists
             lowerCamelCase__		:				int    =  directed





       def 						lowerCAmelCase     (   self							:			List[Any]					,      __lowerCamelCase							:			T					,      __lowerCamelCase							:			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(__lowerCamelCase       )
                         self.adj_list[destination_vertex].append(__lowerCamelCase       )
                   # 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(__lowerCamelCase       )
                         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(__lowerCamelCase       )
                         lowerCamelCase__		:				Any    =  [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__		:				Optional[int]    =  [destination_vertex]
                         lowerCamelCase__		:				List[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(__lowerCamelCase       )
                   # 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(__lowerCamelCase       )
                         lowerCamelCase__		:				Union[str, 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__		:				List[str]    =  [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__		:				Dict    =  []

             return self





       def __repr__(   self							:			Tuple       ):


             '''simple docstring'''



             return pformat(self.adj_list       )






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A      :    Union[str, Any]		=					logging.get_logger(__name__)

A      :    Optional[Any]		=					{
    "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.json",
    "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/config.json",
    "xlm-roberta-large-finetuned-conll02-dutch": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll02-spanish": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-english": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-german": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"
    ),
}







class 			_lowercase (							lowercase__):


       """simple docstring"""




       A__											=			"xlm-roberta"





       def __init__(   self							:			Union[str, Any]					,      __lowerCamelCase							:			Optional[Any]=30522					,      __lowerCamelCase							:			List[Any]=768					,      __lowerCamelCase							:			Union[str, Any]=12					,      __lowerCamelCase							:			int=12					,      __lowerCamelCase							:			Dict=3072					,      __lowerCamelCase							:			Optional[int]="gelu"					,      __lowerCamelCase							:			Optional[Any]=0.1					,      __lowerCamelCase							:			Tuple=0.1					,      __lowerCamelCase							:			str=512					,      __lowerCamelCase							:			Optional[Any]=2					,      __lowerCamelCase							:			Dict=0.0_2					,      __lowerCamelCase							:			List[str]=1E-1_2					,      __lowerCamelCase							:			Optional[int]=1					,      __lowerCamelCase							:			Union[str, Any]=0					,      __lowerCamelCase							:			Optional[int]=2					,      __lowerCamelCase							:			Dict="absolute"					,      __lowerCamelCase							:			Optional[Any]=True					,      __lowerCamelCase							:			Tuple=None					,      **__lowerCamelCase							:			int					,      ):


             '''simple docstring'''



             super().__init__(pad_token_id=__lowerCamelCase					,      bos_token_id=__lowerCamelCase					,      eos_token_id=__lowerCamelCase					,      **__lowerCamelCase       )

             lowerCamelCase__		:				str    =  vocab_size
             lowerCamelCase__		:				Any    =  hidden_size
             lowerCamelCase__		:				Optional[Any]    =  num_hidden_layers
             lowerCamelCase__		:				Union[str, Any]    =  num_attention_heads
             lowerCamelCase__		:				Any    =  hidden_act
             lowerCamelCase__		:				str    =  intermediate_size
             lowerCamelCase__		:				Optional[int]    =  hidden_dropout_prob
             lowerCamelCase__		:				Any    =  attention_probs_dropout_prob
             lowerCamelCase__		:				Union[str, Any]    =  max_position_embeddings
             lowerCamelCase__		:				List[str]    =  type_vocab_size
             lowerCamelCase__		:				Tuple    =  initializer_range
             lowerCamelCase__		:				Tuple    =  layer_norm_eps
             lowerCamelCase__		:				Any    =  position_embedding_type
             lowerCamelCase__		:				Any    =  use_cache
             lowerCamelCase__		:				Any    =  classifier_dropout







class 			_lowercase (							lowercase__):


       """simple docstring"""




       @property
       def 						lowerCAmelCase     (   self							:			Union[str, Any]       ):


             '''simple docstring'''



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


