

'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


A_       						=							logging.get_logger(__name__)

A_       						=							{
    "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 							_snake_case (       _a						):
   _A       :     Optional[int]       =					'''xlm-roberta'''
   def __init__( self			:      List[Any]     ,SCREAMING_SNAKE_CASE__			:      List[str]=30_522     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]=768     ,SCREAMING_SNAKE_CASE__			:      str=12     ,SCREAMING_SNAKE_CASE__			:      Dict=12     ,SCREAMING_SNAKE_CASE__			:      int=3_072     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]="gelu"     ,SCREAMING_SNAKE_CASE__			:      Tuple=0.1     ,SCREAMING_SNAKE_CASE__			:      Dict=0.1     ,SCREAMING_SNAKE_CASE__			:      List[Any]=512     ,SCREAMING_SNAKE_CASE__			:      int=2     ,SCREAMING_SNAKE_CASE__			:      Any=0.02     ,SCREAMING_SNAKE_CASE__			:      Optional[int]=1e-12     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]=1     ,SCREAMING_SNAKE_CASE__			:      Dict=0     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]=2     ,SCREAMING_SNAKE_CASE__			:      Dict="absolute"     ,SCREAMING_SNAKE_CASE__			:      List[str]=True     ,SCREAMING_SNAKE_CASE__			:      List[str]=None     ,**SCREAMING_SNAKE_CASE__			:      Any     ,):
     super().__init__(pad_token_id=__A     ,bos_token_id=__A     ,eos_token_id=__A     ,**__A							)

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





class 							_snake_case (       _a						):
   @property
   def     __UpperCamelCase						( self			:      Union[str, Any]							):
     if self.task == "multiple-choice":
       SCREAMING_SNAKE_CASE:Any						      =					{0: "batch", 1: "choice", 2: "sequence"}
     else:
       SCREAMING_SNAKE_CASE:Optional[Any]						      =					{0: "batch", 1: "sequence"}
     return OrderedDict(
         [
             ("input_ids", dynamic_axis),
             ("attention_mask", dynamic_axis),
         ]							)









'''simple docstring'''

import inspect
import re
from hashlib import shaaaa
from typing import Dict, List

from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql  # noqa F401
from .text import text





def    A_  ( snake_case ):
  SCREAMING_SNAKE_CASE:List[Any]						      =					[]
  for line in lines:
    SCREAMING_SNAKE_CASE:Any						      =					re.sub(r"#.*"      ,       ""      ,       snake_case )  # remove comments
    if line:
      filtered_lines.append(snake_case )
  SCREAMING_SNAKE_CASE:int						      =					"\n".join(snake_case )

  # Make a hash from all this code
  SCREAMING_SNAKE_CASE:str						      =					full_str.encode("utf-8" )
  return shaaaa(snake_case ).hexdigest()


# get importable module names and hash for caching
A_       						=							{
    "csv": (csv.__name__, _hash_python_lines(inspect.getsource(csv).splitlines())),
    "json": (json.__name__, _hash_python_lines(inspect.getsource(json).splitlines())),
    "pandas": (pandas.__name__, _hash_python_lines(inspect.getsource(pandas).splitlines())),
    "parquet": (parquet.__name__, _hash_python_lines(inspect.getsource(parquet).splitlines())),
    "arrow": (arrow.__name__, _hash_python_lines(inspect.getsource(arrow).splitlines())),
    "text": (text.__name__, _hash_python_lines(inspect.getsource(text).splitlines())),
    "imagefolder": (imagefolder.__name__, _hash_python_lines(inspect.getsource(imagefolder).splitlines())),
    "audiofolder": (audiofolder.__name__, _hash_python_lines(inspect.getsource(audiofolder).splitlines())),
}

# Used to infer the module to use based on the data files extensions
A_       						=							{
    ".csv": ("csv", {}),
    ".tsv": ("csv", {"sep": "\t"}),
    ".json": ("json", {}),
    ".jsonl": ("json", {}),
    ".parquet": ("parquet", {}),
    ".arrow": ("arrow", {}),
    ".txt": ("text", {}),
}
_EXTENSION_TO_MODULE.update({ext: ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext: ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ("audiofolder", {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
A_       						=							{"imagefolder", "audiofolder"}

# Used to filter data files based on extensions given a module name
A_       						=							{}
for _ext, (_module, _) in _EXTENSION_TO_MODULE.items():
    _MODULE_TO_EXTENSIONS.setdefault(_module, []).append(_ext)

_MODULE_TO_EXTENSIONS["imagefolder"].append(".zip")


_MODULE_TO_EXTENSIONS["audiofolder"].append(".zip")






