from typing import Mapping

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


snake_case__				= logging.get_logger(__name__)

snake_case__				= {
    't5-small': 'https://huggingface.co/t5-small/resolve/main/config.json',
    't5-base': 'https://huggingface.co/t5-base/resolve/main/config.json',
    't5-large': 'https://huggingface.co/t5-large/resolve/main/config.json',
    't5-3b': 'https://huggingface.co/t5-3b/resolve/main/config.json',
    't5-11b': 'https://huggingface.co/t5-11b/resolve/main/config.json',
}



class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     A_										=  't5'
     A_										=  ['past_key_values']
     A_										=  {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}



     def __init__(					self				,				A_=3_21_28				,				A_=5_12				,				A_=64				,				A_=20_48				,				A_=6				,				A_=None				,				A_=8				,				A_=32				,				A_=1_28				,				A_=0.1				,				A_=1E-6				,				A_=1.0				,				A_="relu"				,				A_=True				,				A_=True				,				A_=0				,				A_=1				,				**A_				,				) ->				Union[str, Any]:






           """simple docstring"""
           _lowerCamelCase			    =				vocab_size
           _lowerCamelCase			    =				d_model
           _lowerCamelCase			    =				d_kv
           _lowerCamelCase			    =				d_ff
           _lowerCamelCase			    =				num_layers
           _lowerCamelCase			    =				(
               num_decoder_layers if num_decoder_layers is not None else self.num_layers
           )  # default = symmetry
           _lowerCamelCase			    =				num_heads
           _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			    =				use_cache

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

           if len(A_						) > 1 and act_info[0] != "gated" or len(A_						) > 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=A_				,				eos_token_id=A_				,				is_encoder_decoder=A_				,				**A_				,				)





class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     @property
     def 		UpperCamelCase_						(					self						) ->				Mapping[str, Mapping[int, 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_(A_				,				direction='''inputs'''						)

           return common_inputs





     @property
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           return 13


def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase		)						->    bool:



      '''simple docstring'''

      _lowerCamelCase			    =				len(__UpperCAmelCase		)
      _lowerCamelCase			    =				[[False] * (required_sum + 1) for _ in range(arr_len + 1		)]

      # for each arr value, a sum of zero(0) can be formed by not taking any element
      # hence True/1
      for i in range(arr_len + 1		):
            _lowerCamelCase			    =				True

      # sum is not zero and set is empty then false
      for i in range(1 ,						required_sum + 1		):
            _lowerCamelCase			    =				False

      for i in range(1 ,						arr_len + 1		):
            for j in range(1 ,						required_sum + 1		):
                  if arr[i - 1] > j:
                        _lowerCamelCase			    =				subset[i - 1][j]
                  if arr[i - 1] <= j:
                        _lowerCamelCase			    =				subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

      return subset[arr_len][required_sum]


if __name__ == "__main__":
     import doctest

     doctest.testmod()