


"""simple docstring"""






# Lint as: python3

import hashlib
from typing import Union
def    A_ ( _lowerCAmelCase  :       Any							):






     """simple docstring"""

     if isinstance(lowerCAmelCase__,  lowerCAmelCase__							):
          # Data already in bytes, returns as it as
          return hash_data
     elif isinstance(lowerCAmelCase__,  lowerCAmelCase__							):
          # We keep the data as it as for it ot be later encoded to UTF-8
          # However replace `\\` with `/` for Windows compatibility
          _a     						=					hash_data.replace('''\\''',  '''/'''							)
     elif isinstance(lowerCAmelCase__,  lowerCAmelCase__							):
          _a     						=					str(lowerCAmelCase__							)
     else:
          # If data is not of the required type, raise error
          raise InvalidKeyError(lowerCAmelCase__							)

     return hash_data.encode('''utf-8'''							)


class      __lowerCamelCase	(       a__					):

     '''simple docstring'''


     def __init__(   self     ,					__UpperCAmelCase				)							->				int:
          _a     						=					'''\nFAILURE TO GENERATE DATASET: Invalid key type detected'''
          _a     						=					F'\nFound Key {hash_data} of type {type(lowercase__				)}'
          _a     						=					'''\nKeys should be either str, int or bytes type'''
          super().__init__(F'{self.prefix}{self.err_msg}{self.suffix}'				)







class      __lowerCamelCase	(       a__					):

     '''simple docstring'''


     def __init__(   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=""				)							->				List[Any]:
          _a     						=					key
          _a     						=					duplicate_key_indices
          _a     						=					fix_msg
          _a     						=					'''Found multiple examples generated with the same key'''
          if len(lowercase__				) <= 20:
               _a     						=					F'\nThe examples at index {", ".join(lowercase__				)} have the key {key}'
          else:
               _a     						=					F'\nThe examples at index {", ".join(duplicate_key_indices[:20]				)}... ({len(lowercase__				) - 20} more) have the key {key}'
          _a     						=					'''\n''' + fix_msg if fix_msg else ''''''
          super().__init__(F'{self.prefix}{self.err_msg}{self.suffix}'				)







class      __lowerCamelCase	:

     '''simple docstring'''


     def __init__(   self     ,					__UpperCAmelCase				)							->				int:
          _a     						=					hashlib.mda(_as_bytes(lowercase__				)				)





     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				Any:
          _a     						=					self._split_mda.copy()
          _a     						=					_as_bytes(lowercase__				)
          mda.update(lowercase__				)
          # Convert to integer with hexadecimal conversion
          return int(mda.hexdigest()     ,					16				)
from typing import Mapping

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


lowerCAmelCase__      		=					logging.get_logger(__name__)

lowerCAmelCase__      		=					{
    'google/long-t5-local-base': 'https://huggingface.co/google/long-t5-local-base/blob/main/config.json',
    'google/long-t5-local-large': 'https://huggingface.co/google/long-t5-local-large/blob/main/config.json',
    'google/long-t5-tglobal-base': 'https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json',
    'google/long-t5-tglobal-large': 'https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json',
}
class 							a_					(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 UpperCAmelCase_      					=   'longt5'
 UpperCAmelCase_      					=   ['past_key_values']
 UpperCAmelCase_      					=   {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}




 def __init__(     self   :    Optional[Any]     ,       lowercase__   :    Union[str, Any]=32_128     ,       lowercase__   :    Union[str, Any]=512     ,       lowercase__   :    List[Any]=64     ,       lowercase__   :    Tuple=2_048     ,       lowercase__   :    List[Any]=6     ,       lowercase__   :    Any=None     ,       lowercase__   :    List[str]=8     ,       lowercase__   :    str=127     ,       lowercase__   :    Any=16     ,       lowercase__   :    str=32     ,       lowercase__   :    str=128     ,       lowercase__   :    Union[str, Any]=0.1     ,       lowercase__   :    List[Any]=1e-6     ,       lowercase__   :    Optional[Any]=1.0     ,       lowercase__   :    str="relu"     ,       lowercase__   :    List[str]=True     ,       lowercase__   :    Any="local"     ,       lowercase__   :    str=True     ,       lowercase__   :    Union[str, Any]=0     ,       lowercase__   :    Optional[int]=1     ,       **lowercase__   :    str     ,       ):







        '''simple docstring'''



        lowerCAmelCase__	      =   vocab_size
        lowerCAmelCase__	      =   d_model
        lowerCAmelCase__	      =   d_kv
        lowerCAmelCase__	      =   d_ff
        lowerCAmelCase__	      =   num_layers
        # default = symmetry
        lowerCAmelCase__	      =   num_decoder_layers if num_decoder_layers is not None else self.num_layers
        lowerCAmelCase__	      =   num_heads
        lowerCAmelCase__	      =   local_radius
        lowerCAmelCase__	      =   global_block_size
        lowerCAmelCase__	      =   relative_attention_num_buckets
        lowerCAmelCase__	      =   relative_attention_max_distance
        lowerCAmelCase__	      =   dropout_rate
        lowerCAmelCase__	      =   layer_norm_epsilon
        lowerCAmelCase__	      =   initializer_factor
        lowerCAmelCase__	      =   feed_forward_proj
        lowerCAmelCase__	      =   encoder_attention_type
        lowerCAmelCase__	      =   use_cache

        lowerCAmelCase__	      =   self.feed_forward_proj.split('-')
        lowerCAmelCase__	      =   act_info[-1]
        lowerCAmelCase__	      =   act_info[0] == 'gated'

        if len(lowercase__) > 1 and act_info[0] != "gated" or len(lowercase__) > 2:
               raise ValueError(
                   F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                   'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
                   '\'gated-gelu\' or \'relu\'')

        # for backwards compatibility
        if feed_forward_proj == "gated-gelu":
               lowerCAmelCase__	      =   'gelu_new'

        super().__init__(
            pad_token_id=lowercase__     ,       eos_token_id=lowercase__     ,       is_encoder_decoder=lowercase__     ,       **lowercase__     ,       )






class 							a_					(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 @property
 def 						__snake_case		(     self   :    str):







        '''simple docstring'''



        lowerCAmelCase__	      =   {
            'input_ids': {0: 'batch', 1: 'encoder_sequence'},
            'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
        }
        if self.use_past:
               lowerCAmelCase__	      =   'past_encoder_sequence + sequence'
               lowerCAmelCase__	      =   {0: 'batch'}
               lowerCAmelCase__	      =   {0: 'batch', 1: 'past_decoder_sequence + sequence'}
        else:
               lowerCAmelCase__	      =   {0: 'batch', 1: 'decoder_sequence'}
               lowerCAmelCase__	      =   {0: 'batch', 1: 'decoder_sequence'}

        if self.use_past:
               self.fill_with_past_key_values_(lowercase__     ,       direction='inputs')

        return common_inputs




 @property
 def 						__snake_case		(     self   :    Any):







        '''simple docstring'''



        return 13
