




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


lowerCamelCase__					:  str      							=				logging.get_logger(__name__)

lowerCamelCase__					:  Tuple      							=				{
    'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
    'funnel-transformer/small-base': 'https://huggingface.co/funnel-transformer/small-base/resolve/main/config.json',
    'funnel-transformer/medium': 'https://huggingface.co/funnel-transformer/medium/resolve/main/config.json',
    'funnel-transformer/medium-base': 'https://huggingface.co/funnel-transformer/medium-base/resolve/main/config.json',
    'funnel-transformer/intermediate': (
        'https://huggingface.co/funnel-transformer/intermediate/resolve/main/config.json'
    ),
    'funnel-transformer/intermediate-base': (
        'https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/config.json'
    ),
    'funnel-transformer/large': 'https://huggingface.co/funnel-transformer/large/resolve/main/config.json',
    'funnel-transformer/large-base': 'https://huggingface.co/funnel-transformer/large-base/resolve/main/config.json',
    'funnel-transformer/xlarge': 'https://huggingface.co/funnel-transformer/xlarge/resolve/main/config.json',
    'funnel-transformer/xlarge-base': 'https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/config.json',
}





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 lowercase_							       =       "funnel"
 lowercase_							       =       {
     "hidden_size": "d_model",
     "num_attention_heads": "n_head",
 }



 def __init__(				self    :						int							,							_lowerCAmelCase    :						Optional[int]=30_522							,							_lowerCAmelCase    :						List[str]=[4, 4, 4]							,							_lowerCAmelCase    :						Tuple=None							,							_lowerCAmelCase    :						Optional[int]=2							,							_lowerCAmelCase    :						int=768							,							_lowerCAmelCase    :						Optional[Any]=12							,							_lowerCAmelCase    :						Optional[Any]=64							,							_lowerCAmelCase    :						Optional[Any]=3_072							,							_lowerCAmelCase    :						List[str]="gelu_new"							,							_lowerCAmelCase    :						Any=0.1							,							_lowerCAmelCase    :						int=0.1							,							_lowerCAmelCase    :						Tuple=0.0							,							_lowerCAmelCase    :						List[Any]=0.1							,							_lowerCAmelCase    :						Dict=None							,							_lowerCAmelCase    :						str=1E-9							,							_lowerCAmelCase    :						Any="mean"							,							_lowerCAmelCase    :						Union[str, Any]="relative_shift"							,							_lowerCAmelCase    :						Optional[Any]=True							,							_lowerCAmelCase    :						Dict=True							,							_lowerCAmelCase    :						Tuple=True							,							**_lowerCAmelCase    :						Optional[Any]							,							):
       SCREAMING_SNAKE_CASE_      		=     vocab_size
       SCREAMING_SNAKE_CASE_      		=     block_sizes
       SCREAMING_SNAKE_CASE_      		=     [1] * len(_lowerCAmelCase		) if block_repeats is None else block_repeats
       assert len(_lowerCAmelCase		) == len(
           self.block_repeats		), "`block_sizes` and `block_repeats` should have the same length."
       SCREAMING_SNAKE_CASE_      		=     num_decoder_layers
       SCREAMING_SNAKE_CASE_      		=     d_model
       SCREAMING_SNAKE_CASE_      		=     n_head
       SCREAMING_SNAKE_CASE_      		=     d_head
       SCREAMING_SNAKE_CASE_      		=     d_inner
       SCREAMING_SNAKE_CASE_      		=     hidden_act
       SCREAMING_SNAKE_CASE_      		=     hidden_dropout
       SCREAMING_SNAKE_CASE_      		=     attention_dropout
       SCREAMING_SNAKE_CASE_      		=     activation_dropout
       SCREAMING_SNAKE_CASE_      		=     initializer_range
       SCREAMING_SNAKE_CASE_      		=     initializer_std
       SCREAMING_SNAKE_CASE_      		=     layer_norm_eps
       assert pooling_type in [
           "mean",
           "max",
       ], F"Got {pooling_type} for `pooling_type` but only 'mean' and 'max' are supported."
       SCREAMING_SNAKE_CASE_      		=     pooling_type
       assert attention_type in [
           "relative_shift",
           "factorized",
       ], F"Got {attention_type} for `attention_type` but only 'relative_shift' and 'factorized' are supported."
       SCREAMING_SNAKE_CASE_      		=     attention_type
       SCREAMING_SNAKE_CASE_      		=     separate_cls
       SCREAMING_SNAKE_CASE_      		=     truncate_seq
       SCREAMING_SNAKE_CASE_      		=     pool_q_only

       super().__init__(**_lowerCAmelCase		)



 @property
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       return sum(self.block_sizes		)



 @num_hidden_layers.setter
 def  lowerCAmelCase_    (				self    :						int							,							_lowerCAmelCase    :						List[Any]		):
       raise NotImplementedError(
           'This model does not support the setting of `num_hidden_layers`. Please set `block_sizes`.'		)



 @property
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       return len(self.block_sizes		)




 @num_blocks.setter
 def  lowerCAmelCase_    (				self    :						Dict							,							_lowerCAmelCase    :						Union[str, Any]		):
       raise NotImplementedError('This model does not support the setting of `num_blocks`. Please set `block_sizes`.'		)





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


lowerCamelCase__					:  str      							=				logging.get_logger(__name__)

lowerCamelCase__					:  Tuple      							=				{
    'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
    'funnel-transformer/small-base': 'https://huggingface.co/funnel-transformer/small-base/resolve/main/config.json',
    'funnel-transformer/medium': 'https://huggingface.co/funnel-transformer/medium/resolve/main/config.json',
    'funnel-transformer/medium-base': 'https://huggingface.co/funnel-transformer/medium-base/resolve/main/config.json',
    'funnel-transformer/intermediate': (
        'https://huggingface.co/funnel-transformer/intermediate/resolve/main/config.json'
    ),
    'funnel-transformer/intermediate-base': (
        'https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/config.json'
    ),
    'funnel-transformer/large': 'https://huggingface.co/funnel-transformer/large/resolve/main/config.json',
    'funnel-transformer/large-base': 'https://huggingface.co/funnel-transformer/large-base/resolve/main/config.json',
    'funnel-transformer/xlarge': 'https://huggingface.co/funnel-transformer/xlarge/resolve/main/config.json',
    'funnel-transformer/xlarge-base': 'https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/config.json',
}





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 lowercase_							       =       "funnel"
 lowercase_							       =       {
     "hidden_size": "d_model",
     "num_attention_heads": "n_head",
 }



 def __init__(				self    :						int							,							_lowerCAmelCase    :						Optional[int]=30_522							,							_lowerCAmelCase    :						List[str]=[4, 4, 4]							,							_lowerCAmelCase    :						Tuple=None							,							_lowerCAmelCase    :						Optional[int]=2							,							_lowerCAmelCase    :						int=768							,							_lowerCAmelCase    :						Optional[Any]=12							,							_lowerCAmelCase    :						Optional[Any]=64							,							_lowerCAmelCase    :						Optional[Any]=3_072							,							_lowerCAmelCase    :						List[str]="gelu_new"							,							_lowerCAmelCase    :						Any=0.1							,							_lowerCAmelCase    :						int=0.1							,							_lowerCAmelCase    :						Tuple=0.0							,							_lowerCAmelCase    :						List[Any]=0.1							,							_lowerCAmelCase    :						Dict=None							,							_lowerCAmelCase    :						str=1E-9							,							_lowerCAmelCase    :						Any="mean"							,							_lowerCAmelCase    :						Union[str, Any]="relative_shift"							,							_lowerCAmelCase    :						Optional[Any]=True							,							_lowerCAmelCase    :						Dict=True							,							_lowerCAmelCase    :						Tuple=True							,							**_lowerCAmelCase    :						Optional[Any]							,							):
       SCREAMING_SNAKE_CASE_      		=     vocab_size
       SCREAMING_SNAKE_CASE_      		=     block_sizes
       SCREAMING_SNAKE_CASE_      		=     [1] * len(_lowerCAmelCase		) if block_repeats is None else block_repeats
       assert len(_lowerCAmelCase		) == len(
           self.block_repeats		), "`block_sizes` and `block_repeats` should have the same length."
       SCREAMING_SNAKE_CASE_      		=     num_decoder_layers
       SCREAMING_SNAKE_CASE_      		=     d_model
       SCREAMING_SNAKE_CASE_      		=     n_head
       SCREAMING_SNAKE_CASE_      		=     d_head
       SCREAMING_SNAKE_CASE_      		=     d_inner
       SCREAMING_SNAKE_CASE_      		=     hidden_act
       SCREAMING_SNAKE_CASE_      		=     hidden_dropout
       SCREAMING_SNAKE_CASE_      		=     attention_dropout
       SCREAMING_SNAKE_CASE_      		=     activation_dropout
       SCREAMING_SNAKE_CASE_      		=     initializer_range
       SCREAMING_SNAKE_CASE_      		=     initializer_std
       SCREAMING_SNAKE_CASE_      		=     layer_norm_eps
       assert pooling_type in [
           "mean",
           "max",
       ], F"Got {pooling_type} for `pooling_type` but only 'mean' and 'max' are supported."
       SCREAMING_SNAKE_CASE_      		=     pooling_type
       assert attention_type in [
           "relative_shift",
           "factorized",
       ], F"Got {attention_type} for `attention_type` but only 'relative_shift' and 'factorized' are supported."
       SCREAMING_SNAKE_CASE_      		=     attention_type
       SCREAMING_SNAKE_CASE_      		=     separate_cls
       SCREAMING_SNAKE_CASE_      		=     truncate_seq
       SCREAMING_SNAKE_CASE_      		=     pool_q_only

       super().__init__(**_lowerCAmelCase		)



 @property
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       return sum(self.block_sizes		)



 @num_hidden_layers.setter
 def  lowerCAmelCase_    (				self    :						int							,							_lowerCAmelCase    :						List[Any]		):
       raise NotImplementedError(
           'This model does not support the setting of `num_hidden_layers`. Please set `block_sizes`.'		)



 @property
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       return len(self.block_sizes		)




 @num_blocks.setter
 def  lowerCAmelCase_    (				self    :						Dict							,							_lowerCAmelCase    :						Union[str, Any]		):
       raise NotImplementedError('This model does not support the setting of `num_blocks`. Please set `block_sizes`.'		)