




'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


_lowercase  =			logging.get_logger(__name__)

_lowercase  =			{
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}
class 						a_				(			UpperCAmelCase__						):
	lowercase_       :     Optional[Any]			  =      '''camembert'''




	def __init__(       self     :  Dict       ,		__lowerCAmelCase     :  List[str]=3_0_5_2_2       ,		__lowerCAmelCase     :  Optional[Any]=7_6_8       ,		__lowerCAmelCase     :  Optional[Any]=1_2       ,		__lowerCAmelCase     :  Union[str, Any]=1_2       ,		__lowerCAmelCase     :  str=3_0_7_2       ,		__lowerCAmelCase     :  Union[str, Any]="gelu"       ,		__lowerCAmelCase     :  Optional[Any]=0.1       ,		__lowerCAmelCase     :  Dict=0.1       ,		__lowerCAmelCase     :  List[str]=5_1_2       ,		__lowerCAmelCase     :  Any=2       ,		__lowerCAmelCase     :  Tuple=0.02       ,		__lowerCAmelCase     :  List[Any]=1E-12       ,		__lowerCAmelCase     :  Dict=1       ,		__lowerCAmelCase     :  Optional[int]=0       ,		__lowerCAmelCase     :  Optional[Any]=2       ,		__lowerCAmelCase     :  List[str]="absolute"       ,		__lowerCAmelCase     :  Any=True       ,		__lowerCAmelCase     :  Tuple=None       ,		**__lowerCAmelCase     :  Union[str, Any]       ,		):
							super().__init__(pad_token_id=__lowerCAmelCase       ,		bos_token_id=__lowerCAmelCase       ,		eos_token_id=__lowerCAmelCase       ,		**__lowerCAmelCase      )

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





class 						a_				(			UpperCAmelCase__						):




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







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase  =			{
    """configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase  =			[
	    """PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """PegasusXForConditionalGeneration""",
	    """PegasusXModel""",
	    """PegasusXPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_pegasus_x import (
		    PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
		    PegasusXForConditionalGeneration,
		    PegasusXModel,
		    PegasusXPreTrainedModel,
		)


else:
	import sys

	_lowercase  =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

