"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase_    :		Any							=	logging.get_logger(__name__)

lowerCamelCase_    :		Tuple							=	{
    """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 						a__							(       __A		):
			A__    :       Tuple        =      'xmod'



			def __init__(						self				,						UpperCAmelCase=3_0_5_2_2				,						UpperCAmelCase=7_6_8				,						UpperCAmelCase=1_2				,						UpperCAmelCase=1_2				,						UpperCAmelCase=3_0_7_2				,						UpperCAmelCase="gelu"				,						UpperCAmelCase=0.1				,						UpperCAmelCase=0.1				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=2				,						UpperCAmelCase=0.02				,						UpperCAmelCase=1e-12				,						UpperCAmelCase=1				,						UpperCAmelCase=0				,						UpperCAmelCase=2				,						UpperCAmelCase="absolute"				,						UpperCAmelCase=True				,						UpperCAmelCase=None				,						UpperCAmelCase=False				,						UpperCAmelCase=2				,						UpperCAmelCase=False				,						UpperCAmelCase=True				,						UpperCAmelCase=True				,						UpperCAmelCase=("en_XX",)				,						UpperCAmelCase=None				,						**UpperCAmelCase				,						)			->   Union[str, Any]:
								super().__init__(pad_token_id=__lowercase				,						bos_token_id=__lowercase				,						eos_token_id=__lowercase				,						**__lowercase   )

								__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
								__a		 =       pre_norm
								__a		 =       adapter_reduction_factor
								__a		 =       adapter_layer_norm
								__a		 =       adapter_reuse_layer_norm
								__a		 =       ln_before_adapter
								__a		 =       list(__lowercase   )
								__a		 =       default_language






class 						a__							(       __A		):



			@property
			def __SCREAMING_SNAKE_CASE							(						self   )			->   Union[str, Any]:
								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),
								    ]   )





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_    :		Tuple							=	logging.get_logger(__name__)

lowerCamelCase_    :		List[Any]							=	{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}


class 						a__							(       __snake_case		):
			A__    :       Dict        =      'fnet'



			def __init__(						self				,						UpperCAmelCase=3_2_0_0_0				,						UpperCAmelCase=7_6_8				,						UpperCAmelCase=1_2				,						UpperCAmelCase=3_0_7_2				,						UpperCAmelCase="gelu_new"				,						UpperCAmelCase=0.1				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=4				,						UpperCAmelCase=0.02				,						UpperCAmelCase=1e-12				,						UpperCAmelCase=False				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=3				,						UpperCAmelCase=1				,						UpperCAmelCase=2				,						**UpperCAmelCase				,						)			->   Dict:
								super().__init__(pad_token_id=UpperCAmelCase				,						bos_token_id=UpperCAmelCase				,						eos_token_id=UpperCAmelCase				,						**UpperCAmelCase   )

								__a		 =       vocab_size
								__a		 =       max_position_embeddings
								__a		 =       hidden_size
								__a		 =       num_hidden_layers
								__a		 =       intermediate_size
								__a		 =       hidden_act
								__a		 =       hidden_dropout_prob
								__a		 =       initializer_range
								__a		 =       type_vocab_size
								__a		 =       layer_norm_eps
								__a		 =       use_tpu_fourier_optimizations
								__a		 =       tpu_short_seq_length




