




'''simple docstring'''



from typing import Mapping

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


UpperCAmelCase_							:	int	     =		logging.get_logger(__name__)

UpperCAmelCase_							:	Optional[Any]	     =		{
    '''google/umt5-small''': '''https://huggingface.co/google/umt5-small/resolve/main/config.json''',
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}





class      lowerCAmelCase (			__lowerCAmelCase):
       __lowercase	:   List[Any]										=      '''umt5'''
       __lowercase	:   Union[str, Any]										=      ['''past_key_values''']


       def __init__( self     ,	__SCREAMING_SNAKE_CASE=25_0112     ,	__SCREAMING_SNAKE_CASE=512     ,	__SCREAMING_SNAKE_CASE=64     ,	__SCREAMING_SNAKE_CASE=1024     ,	__SCREAMING_SNAKE_CASE=8     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=6     ,	__SCREAMING_SNAKE_CASE=32     ,	__SCREAMING_SNAKE_CASE=128     ,	__SCREAMING_SNAKE_CASE=0.1     ,	__SCREAMING_SNAKE_CASE=1E-6     ,	__SCREAMING_SNAKE_CASE=1.0     ,	__SCREAMING_SNAKE_CASE="gated-gelu"     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE="T5Tokenizer"     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE=0     ,	__SCREAMING_SNAKE_CASE=1     ,	__SCREAMING_SNAKE_CASE=0     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	Union[str, Any]:



            '''simple docstring'''




            super().__init__(
                is_encoder_decoder=__SCREAMING_SNAKE_CASE     ,	tokenizer_class=__SCREAMING_SNAKE_CASE     ,	tie_word_embeddings=__SCREAMING_SNAKE_CASE     ,	pad_token_id=__SCREAMING_SNAKE_CASE     ,	eos_token_id=__SCREAMING_SNAKE_CASE     ,	decoder_start_token_id=__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE     ,	)
            __snake_case            =	vocab_size
            __snake_case            =	d_model
            __snake_case            =	d_kv
            __snake_case            =	d_ff
            __snake_case            =	num_layers
            __snake_case            =	(
                num_decoder_layers if num_decoder_layers is not None else self.num_layers
            )  # default = symmetry
            __snake_case            =	num_heads
            __snake_case            =	relative_attention_num_buckets
            __snake_case            =	relative_attention_max_distance
            __snake_case            =	dropout_rate
            __snake_case            =	layer_norm_epsilon
            __snake_case            =	initializer_factor
            __snake_case            =	feed_forward_proj
            __snake_case            =	use_cache

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

            if len(__SCREAMING_SNAKE_CASE	) > 1 and act_info[0] != "gated" or len(__SCREAMING_SNAKE_CASE	) > 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\''''	)

            if feed_forward_proj == "gated-gelu":
                 __snake_case            =	'''gelu_new'''


       @property
       def    lowerCAmelCase   ( self	)   ->	int:



            '''simple docstring'''




            return self.d_model


       @property
       def    lowerCAmelCase   ( self	)   ->	Any:



            '''simple docstring'''




            return self.num_heads




       @property
       def    lowerCAmelCase   ( self	)   ->	List[Any]:



            '''simple docstring'''




            return self.num_layers





class      lowerCAmelCase (			__lowerCAmelCase):


       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
       def    lowerCAmelCase   ( self	)   ->	Mapping[str, Mapping[int, str]]:



            '''simple docstring'''




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

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

            return common_inputs


       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
       def    lowerCAmelCase   ( self	)   ->	int:



            '''simple docstring'''




            return 13




       @property
       def    lowerCAmelCase   ( self	)   ->	float:



            '''simple docstring'''




            return 5E-4












'''simple docstring'''



def       _UpperCamelCase			(_lowerCamelCase				:  int						)-> int:




     '''simple docstring'''





     __snake_case            =	abs(_lowerCamelCase						)
     __snake_case            =	0
     while n > 0:
          res += n % 10
          n //= 10
     return res







def       _UpperCamelCase			(_lowerCamelCase				:  int						)-> int:




     '''simple docstring'''





     __snake_case            =	abs(_lowerCamelCase						)
     return n if n < 10 else n % 10 + sum_of_digits(n // 10						)







def       _UpperCamelCase			(_lowerCamelCase				:  int						)-> int:




     '''simple docstring'''





     return sum(int(_lowerCamelCase						) for c in str(abs(_lowerCamelCase						)						)						)







def       _UpperCamelCase			()-> None:




     '''simple docstring'''





     from collections.abc import Callable
     from timeit import timeit

     def benchmark_a_function(_lowerCamelCase				:  Callable ,						_lowerCamelCase				:  int						) -> None:
          __snake_case            =	f'''{func.__name__}({value})'''
          __snake_case            =	timeit(f'''__main__.{call}''' ,						setup='''import __main__'''						)
          print(f'''{call:56} = {func(_lowerCamelCase						)} -- {timing:.4f} seconds'''						)

     for value in (26_21_44, 11_25_89_99_06_84_26_24, 1_26_76_50_60_02_28_22_94_01_49_67_03_20_53_76):
          for func in (sum_of_digits, sum_of_digits_recursion, sum_of_digits_compact):
               benchmark_a_function(_lowerCamelCase ,						_lowerCamelCase						)
          print()


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     benchmark()






