


from typing import Callable, Optional, Union

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


__magic_name__       					=      logging.get_logger(__name__)

__magic_name__       					=      {
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}





class    lowerCAmelCase__				(			__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	'''prophetnet'''
						__UpperCAmelCase   :		List[str]  					=	['''past_key_values''']
						__UpperCAmelCase   :		List[str]  					=	{
						    '''num_attention_heads''': '''num_encoder_attention_heads''',
						}




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

							# parameters for prophetnet
							lowerCamelCase_			:							Tuple      =       ngram
							lowerCamelCase_			:							List[Any]      =       num_buckets
							lowerCamelCase_			:							str      =       relative_max_distance
							lowerCamelCase_			:							Tuple      =       disable_ngram_loss
							lowerCamelCase_			:							Any      =       eps

							# 3 Types of Dropout
							lowerCamelCase_			:							Optional[Any]      =       attention_dropout
							lowerCamelCase_			:							Optional[Any]      =       activation_dropout
							lowerCamelCase_			:							Optional[int]      =       dropout

							lowerCamelCase_			:							Any      =       use_cache

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




						@property
						def 					_UpperCamelCase			(   self     ):
							return self.num_encoder_layers + self.num_decoder_layers




						@num_hidden_layers.setter
						def 					_UpperCamelCase			(   self				,							a_     ):
							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, is_vision_available


__magic_name__       					=      {'''configuration_levit''': ['''LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LevitConfig''', '''LevitOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      ['''LevitFeatureExtractor''']
							__magic_name__       					=      ['''LevitImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      [
							    '''LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''LevitForImageClassification''',
							    '''LevitForImageClassificationWithTeacher''',
							    '''LevitModel''',
							    '''LevitPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_levit import LevitFeatureExtractor
														from .image_processing_levit import LevitImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_levit import (
														    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LevitForImageClassification,
														    LevitForImageClassificationWithTeacher,
														    LevitModel,
														    LevitPreTrainedModel,
														)
else:
							import sys

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

