

from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase		       =    logging.get_logger(__name__)

__lowerCamelCase		       =    {
    '''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 					A__      (      _snake_case			):
    lowercase						=		"xlm-roberta"



    def __init__(					self		,				UpperCamelCase__=30522		,				UpperCamelCase__=768		,				UpperCamelCase__=12		,				UpperCamelCase__=12		,				UpperCamelCase__=3072		,				UpperCamelCase__="gelu"		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.1		,				UpperCamelCase__=512		,				UpperCamelCase__=2		,				UpperCamelCase__=0.02		,				UpperCamelCase__=1e-1_2		,				UpperCamelCase__=1		,				UpperCamelCase__=0		,				UpperCamelCase__=2		,				UpperCamelCase__="absolute"		,				UpperCamelCase__=True		,				UpperCamelCase__=None		,				**UpperCamelCase__		,				)						->      Dict:





           '''simple docstring'''
           super().__init__(pad_token_id=UpperCamelCase__		,				bos_token_id=UpperCamelCase__		,				eos_token_id=UpperCamelCase__		,				**UpperCamelCase__       )

           A_						=      vocab_size
           A_						=      hidden_size
           A_						=      num_hidden_layers
           A_						=      num_attention_heads
           A_						=      hidden_act
           A_						=      intermediate_size
           A_						=      hidden_dropout_prob
           A_						=      attention_probs_dropout_prob
           A_						=      max_position_embeddings
           A_						=      type_vocab_size
           A_						=      initializer_range
           A_						=      layer_norm_eps
           A_						=      position_embedding_type
           A_						=      use_cache
           A_						=      classifier_dropout


class 					A__      (      _snake_case			):



    @property
    def 					snake_case_			(					self       )						->      Mapping[str, Mapping[int, str]]:





           '''simple docstring'''
           if self.task == "multiple-choice":
                  A_						=      {0: """batch""", 1: """choice""", 2: """sequence"""}
           else:
                  A_						=      {0: """batch""", 1: """sequence"""}
           return OrderedDict(
               [
                   ("""input_ids""", dynamic_axis),
                   ("""attention_mask""", dynamic_axis),
               ]       )



'''simple docstring'''







import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    '''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
    ''' StableDiffusionImg2ImgPipeline` instead.'''
)
