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


_UpperCamelCase:					Dict     =logging.get_logger(__name__)

_UpperCamelCase:					Any     ={
    'google/pegasus-x-base': 'https://huggingface.co/google/pegasus-x-base/resolve/main/config.json',
    'google/pegasus-x-large': 'https://huggingface.co/google/pegasus-x-large/resolve/main/config.json',
    # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
}





class 						__lowercase(     SCREAMING_SNAKE_CASE   ):


       """simple docstring"""







       UpperCamelCase_				 =							'''pegasus_x'''
       UpperCamelCase_				 =							['''past_key_values''']
       UpperCamelCase_				 =							{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}



       def __init__(     self					:			List[str]  ,      _lowerCAmelCase					:			Dict=9_6103  ,      _lowerCAmelCase					:			Union[str, Any]=1_6384  ,      _lowerCAmelCase					:			Dict=16  ,      _lowerCAmelCase					:			Union[str, Any]=4096  ,      _lowerCAmelCase					:			str=16  ,      _lowerCAmelCase					:			int=16  ,      _lowerCAmelCase					:			List[str]=4096  ,      _lowerCAmelCase					:			str=16  ,      _lowerCAmelCase					:			Union[str, Any]=0.0  ,      _lowerCAmelCase					:			int=0.0  ,      _lowerCAmelCase					:			Any=True  ,      _lowerCAmelCase					:			Optional[int]=True  ,      _lowerCAmelCase					:			int="gelu"  ,      _lowerCAmelCase					:			List[Any]=1024  ,      _lowerCAmelCase					:			Tuple=0.1  ,      _lowerCAmelCase					:			Optional[Any]=0.0  ,      _lowerCAmelCase					:			Union[str, Any]=0.0  ,      _lowerCAmelCase					:			List[str]=0.02  ,      _lowerCAmelCase					:			Optional[int]=0  ,      _lowerCAmelCase					:			str=True  ,      _lowerCAmelCase					:			Optional[int]=0  ,      _lowerCAmelCase					:			Any=1  ,      _lowerCAmelCase					:			Optional[Any]=1  ,      _lowerCAmelCase					:			Optional[Any]=32  ,      _lowerCAmelCase					:			Any=512  ,      _lowerCAmelCase					:			List[Any]=True  ,      **_lowerCAmelCase					:			Any  ,      )					->   str:
         _lowerCAmelCase						=		vocab_size
         _lowerCAmelCase						=		max_position_embeddings
         _lowerCAmelCase						=		d_model
         _lowerCAmelCase						=		encoder_ffn_dim
         _lowerCAmelCase						=		encoder_layers
         _lowerCAmelCase						=		encoder_attention_heads
         _lowerCAmelCase						=		decoder_ffn_dim
         _lowerCAmelCase						=		decoder_layers
         _lowerCAmelCase						=		decoder_attention_heads
         _lowerCAmelCase						=		dropout
         _lowerCAmelCase						=		attention_dropout
         _lowerCAmelCase						=		activation_dropout
         _lowerCAmelCase						=		activation_function
         _lowerCAmelCase						=		init_std
         _lowerCAmelCase						=		encoder_layerdrop
         _lowerCAmelCase						=		decoder_layerdrop
         _lowerCAmelCase						=		use_cache
         _lowerCAmelCase						=		encoder_layers
         _lowerCAmelCase						=		scale_embedding  # scale factor will be sqrt(d_model) if True

         _lowerCAmelCase						=		num_global_tokens
         _lowerCAmelCase						=		block_size
         _lowerCAmelCase						=		stagger_local_blocks

         super().__init__(
             pad_token_id=_lowerCAmelCase  ,      eos_token_id=_lowerCAmelCase  ,      is_encoder_decoder=_lowerCAmelCase  ,      decoder_start_token_id=_lowerCAmelCase  ,      forced_eos_token_id=_lowerCAmelCase  ,      **_lowerCAmelCase  ,      )



       @property
       def SCREAMING_SNAKE_CASE_				(     self					:			int       )					->   int:
         return self.encoder_attention_heads






       @property
       def SCREAMING_SNAKE_CASE_				(     self					:			Any       )					->   int:
         return self.d_model


import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


_UpperCamelCase:					List[Any]     =TypeVar('T', bound='TaskTemplate')





@dataclass(frozen=SCREAMING_SNAKE_CASE   )
class 						__lowercase(     abc.ABC   ):


       """simple docstring"""







       UpperCamelCase_				 =							42
       UpperCamelCase_				 =							42
       UpperCamelCase_				 =							42



       def SCREAMING_SNAKE_CASE_				(     self					:			T  ,      _lowerCAmelCase					:			Features       )					->   T:
         return copy.deepcopy(self       )



       @property
       def SCREAMING_SNAKE_CASE_				(     self					:			str       )					->   Features:
         return Features(**self.input_schema  ,      **self.label_schema       )



       @property
       @abc.abstractmethod
       def SCREAMING_SNAKE_CASE_				(     self					:			Dict       )					->   Dict[str, str]:
         raise NotImplementedError






       @classmethod
       def SCREAMING_SNAKE_CASE_				(     cls					:			Type[T]  ,      _lowerCAmelCase					:			dict       )					->   T:
         _lowerCAmelCase						=		{f.name for f in dataclasses.fields(cls       )}
         return cls(**{k: v for k, v in template_dict.items() if k in field_names}       )
