

"""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_   :   Dict        =       logging.get_logger(__name__)

snake_case_   :   str        =       {
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}







class       snake_case__  ( lowerCAmelCase_     ):
			SCREAMING_SNAKE_CASE__     				=						'''xmod'''







			def __init__(			self			: Tuple			,  lowercase			: List[str]=3_05_22			,  lowercase			: List[Any]=7_68			,  lowercase			: List[Any]=12			,  lowercase			: List[str]=12			,  lowercase			: Any=30_72			,  lowercase			: List[Any]="gelu"			,  lowercase			: Optional[Any]=0.1			,  lowercase			: Optional[int]=0.1			,  lowercase			: Optional[int]=5_12			,  lowercase			: Dict=2			,  lowercase			: Tuple=0.0_2			,  lowercase			: Optional[int]=1E-12			,  lowercase			: Any=1			,  lowercase			: Optional[int]=0			,  lowercase			: Tuple=2			,  lowercase			: Union[str, Any]="absolute"			,  lowercase			: Optional[int]=True			,  lowercase			: List[Any]=None			,  lowercase			: List[Any]=False			,  lowercase			: Union[str, Any]=2			,  lowercase			: str=False			,  lowercase			: Any=True			,  lowercase			: Optional[Any]=True			,  lowercase			: List[str]=("en_XX",)			,  lowercase			: Tuple=None			,  **lowercase			: Tuple			,  ):





								'''simple docstring'''



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

								UpperCAmelCase			:   str      =				vocab_size
								UpperCAmelCase			:   Union[str, Any]      =				hidden_size
								UpperCAmelCase			:   str      =				num_hidden_layers
								UpperCAmelCase			:   Optional[Any]      =				num_attention_heads
								UpperCAmelCase			:   Any      =				hidden_act
								UpperCAmelCase			:   int      =				intermediate_size
								UpperCAmelCase			:   Dict      =				hidden_dropout_prob
								UpperCAmelCase			:   Union[str, Any]      =				attention_probs_dropout_prob
								UpperCAmelCase			:   List[str]      =				max_position_embeddings
								UpperCAmelCase			:   Tuple      =				type_vocab_size
								UpperCAmelCase			:   Optional[int]      =				initializer_range
								UpperCAmelCase			:   int      =				layer_norm_eps
								UpperCAmelCase			:   List[Any]      =				position_embedding_type
								UpperCAmelCase			:   List[str]      =				use_cache
								UpperCAmelCase			:   Union[str, Any]      =				classifier_dropout
								UpperCAmelCase			:   List[str]      =				pre_norm
								UpperCAmelCase			:   int      =				adapter_reduction_factor
								UpperCAmelCase			:   Optional[Any]      =				adapter_layer_norm
								UpperCAmelCase			:   Union[str, Any]      =				adapter_reuse_layer_norm
								UpperCAmelCase			:   List[Any]      =				ln_before_adapter
								UpperCAmelCase			:   Tuple      =				list(lowercase  )
								UpperCAmelCase			:   List[Any]      =				default_language







class       snake_case__  ( lowerCAmelCase_     ):







			@property
			def 			__lowerCAmelCase				(			self			: Optional[int]  ):





								'''simple docstring'''



								if self.task == "multiple-choice":
													UpperCAmelCase			:   List[Any]      =				{0: "batch", 1: "choice", 2: "sequence"}
								else:
													UpperCAmelCase			:   Tuple      =				{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_tokenizers_available, is_torch_available


snake_case_   :   Dict        =       {
    """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
    """tokenization_mvp""": ["""MvpTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   List[Any]        =       ["""MvpTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   Any        =       [
	    """MVP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """MvpForCausalLM""",
	    """MvpForConditionalGeneration""",
	    """MvpForQuestionAnswering""",
	    """MvpForSequenceClassification""",
	    """MvpModel""",
	    """MvpPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
	from .tokenization_mvp import MvpTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_mvp_fast import MvpTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mvp import (
		    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MvpForCausalLM,
		    MvpForConditionalGeneration,
		    MvpForQuestionAnswering,
		    MvpForSequenceClassification,
		    MvpModel,
		    MvpPreTrainedModel,
		)

else:
	import sys

	snake_case_   :   List[str]        =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


