'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """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__     (				_lowercase	):
	__magic_name__		:    Dict	    =     "xlm-roberta"


	def __init__(self : Dict,					__UpperCAmelCase : Optional[int]=30522,					__UpperCAmelCase : Tuple=768,					__UpperCAmelCase : str=12,					__UpperCAmelCase : Union[str, Any]=12,					__UpperCAmelCase : List[str]=3072,					__UpperCAmelCase : int="gelu",					__UpperCAmelCase : Optional[int]=0.1,					__UpperCAmelCase : Tuple=0.1,					__UpperCAmelCase : Union[str, Any]=512,					__UpperCAmelCase : List[str]=2,					__UpperCAmelCase : Optional[int]=0.02,					__UpperCAmelCase : Optional[int]=1e-12,					__UpperCAmelCase : Any=1,					__UpperCAmelCase : int=0,					__UpperCAmelCase : Tuple=2,					__UpperCAmelCase : List[str]="absolute",					__UpperCAmelCase : Optional[int]=True,					__UpperCAmelCase : int=None,					**__UpperCAmelCase : List[Any],					)     ->			Tuple:

					"""simple docstring"""

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

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



class 	a__     (				_lowercase	):


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

					"""simple docstring"""

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









'''simple docstring'''

from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
	from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline




