
"""simple docstring"""


from typing import Callable, Optional, Union

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


_lowercase							      = logging.get_logger(__name__)

_lowercase							      = {
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}







class  lowerCAmelCase_ (					_snake_case			):



						'''simple docstring'''


						_lowerCamelCase:			Tuple					=			'''xlm-prophetnet'''
						_lowerCamelCase:			Dict					=			['''past_key_values''']
						_lowerCamelCase:			List[str]					=			{
						    '''num_attention_heads''': '''num_encoder_attention_heads''',
						}


						def __init__(       self   :					Optional[Any]     ,A_   :					List[Any] = 0.1     ,A_   :					List[Any] = "gelu"     ,A_   :					Optional[int] = 3_0522     ,A_   :					Any = 1024     ,A_   :					Union[str, Any] = 4096     ,A_   :					Any = 12     ,A_   :					Union[str, Any] = 16     ,A_   :					Optional[Any] = 4096     ,A_   :					List[str] = 12     ,A_   :					Tuple = 16     ,A_   :					Any = 0.1     ,A_   :					Any = 0.1     ,A_   :					List[str] = 512     ,A_   :					List[Any] = 0.02     ,A_   :					Dict = True     ,A_   :					Optional[int] = True     ,A_   :					Dict = 0     ,A_   :					Optional[Any] = 2     ,A_   :					Dict = 32     ,A_   :					Tuple = 128     ,A_   :					Dict = False     ,A_   :					Any = 0.0     ,A_   :					Any = True     ,A_   :					List[Any] = 0     ,A_   :					List[Any] = 1     ,A_   :					Any = 2     ,**A_   :					Union[str, Any]     ,)   ->      Tuple:
							A        =      vocab_size
							A        =      hidden_size
							A        =      encoder_ffn_dim
							A        =      num_encoder_layers
							A        =      num_encoder_attention_heads
							A        =      decoder_ffn_dim
							A        =      num_decoder_layers
							A        =      num_decoder_attention_heads
							A        =      max_position_embeddings
							A        =      init_std  # Normal(0, this parameter)
							A        =      activation_function

							# parameters for xlmprophetnet
							A        =      ngram
							A        =      num_buckets
							A        =      relative_max_distance
							A        =      disable_ngram_loss
							A        =      eps

							# 3 Types of Dropout
							A        =      attention_dropout
							A        =      activation_dropout
							A        =      dropout

							A        =      use_cache

							super().__init__(
							    pad_token_id=_UpperCamelCase     ,bos_token_id=_UpperCamelCase     ,eos_token_id=_UpperCamelCase     ,is_encoder_decoder=_UpperCamelCase     ,add_cross_attention=_UpperCamelCase     ,decoder_start_token_id=_UpperCamelCase     ,**_UpperCamelCase     ,)


						@property
						def   _SCREAMING_SNAKE_CASE					(       self   :					Any					)   ->      int:
							return self.num_encoder_layers + self.num_decoder_layers




						@num_hidden_layers.setter
						def   _SCREAMING_SNAKE_CASE					(       self   :					Union[str, Any]     ,A_   :					Dict					)   ->      int:
							raise NotImplementedError(
							    'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
							    ' `num_decoder_layers`.'					)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase								=						{'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ViTMSNModel',
		    'ViTMSNForImageClassification',
		    'ViTMSNPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_msn import (
				    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMSNForImageClassification,
				    ViTMSNModel,
				    ViTMSNPreTrainedModel,
				)

else:
		import sys

		__UpperCAmelCase								=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






