



'''simple docstring'''





from __future__ import annotations





def   a_   (		_UpperCAmelCase    :      str ,_UpperCAmelCase    :      list[str] | None = None				)    ->  list[list[str]]:
      __snake_case :   int													=    word_bank or []
      # create a table
      __snake_case :   int													=    len(_UpperCAmelCase				) + 1

      __snake_case :   list[list[list[str]]]													=    []
      for _ in range(_UpperCAmelCase				):
            table.append([]				)
      # seed value
      __snake_case :   Union[str, Any]													=    [[]]  # because empty string has empty combination

      # iterate through the indices
      for i in range(_UpperCAmelCase				):
            # condition
            if table[i] != []:
                  for word in word_bank:
                        # slice condition
                        if target[i : i + len(_UpperCAmelCase				)] == word:
                              __snake_case :   list[list[str]]													=    [
                                  [word, *way] for way in table[i]
                              ]
                              # adds the word to every combination the current position holds
                              # now,push that combination to the table[i+len(word)]
                              table[i + len(_UpperCAmelCase				)] += new_combinations

    # combinations are in reverse order so reverse for better output
      for combination in table[len(_UpperCAmelCase				)]:
            combination.reverse()

      return table[len(_UpperCAmelCase				)]


if __name__ == "__main__":
    print(all_construct('''jwajalapa''', ['''jwa''', '''j''', '''w''', '''a''', '''la''', '''lapa''']))
    print(all_construct('''rajamati''', ['''s''', '''raj''', '''amat''', '''raja''', '''ma''', '''i''', '''t''']))
    print(
        all_construct(
            '''hexagonosaurus''',
            ['''h''', '''ex''', '''hex''', '''ag''', '''ago''', '''ru''', '''auru''', '''rus''', '''go''', '''no''', '''o''', '''s'''],
        )
    )






'''simple docstring'''





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


UpperCamelCase_    						=       logging.get_logger(__name__)

UpperCamelCase_    						=       {
    """facebook/s2t-wav2vec2-large-en-de""": (
        """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json"""
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}





class 		__SCREAMING_SNAKE_CASE							(			lowercase__      ):
				lowerCamelCase_		       =    'speech_to_text_2'
				lowerCamelCase_		       =    ['past_key_values']
				lowerCamelCase_		       =    {'num_attention_heads': 'decoder_attention_heads', 'hidden_size': 'd_model'}







				def __init__(       self     :		int		,					UpperCAmelCase__     :		Dict=10000		,					UpperCAmelCase__     :		Optional[int]=6		,					UpperCAmelCase__     :		str=2048		,					UpperCAmelCase__     :		Optional[Any]=4		,					UpperCAmelCase__     :		Union[str, Any]=0.0		,					UpperCAmelCase__     :		Optional[Any]=True		,					UpperCAmelCase__     :		Optional[Any]="relu"		,					UpperCAmelCase__     :		List[str]=256		,					UpperCAmelCase__     :		Union[str, Any]=0.1		,					UpperCAmelCase__     :		List[Any]=0.0		,					UpperCAmelCase__     :		Optional[Any]=0.0		,					UpperCAmelCase__     :		Tuple=0.02		,					UpperCAmelCase__     :		int=2		,					UpperCAmelCase__     :		str=True		,					UpperCAmelCase__     :		str=1		,					UpperCAmelCase__     :		Optional[Any]=0		,					UpperCAmelCase__     :		Optional[int]=2		,					UpperCAmelCase__     :		List[Any]=1024		,					**UpperCAmelCase__     :		Dict		,					):
										'''simple docstring'''
										lowercase :							List[str]    		=vocab_size
										lowercase :							Optional[int]    		=d_model
										lowercase :							Optional[Any]    		=decoder_ffn_dim
										lowercase :							Any    		=decoder_layers
										lowercase :							Dict    		=decoder_attention_heads
										lowercase :							List[Any]    		=dropout
										lowercase :							List[Any]    		=attention_dropout
										lowercase :							Any    		=activation_dropout
										lowercase :							Optional[Any]    		=activation_function
										lowercase :							Optional[int]    		=init_std
										lowercase :							Dict    		=decoder_layerdrop
										lowercase :							Optional[int]    		=use_cache
										lowercase :							Optional[Any]    		=decoder_layers
										lowercase :							List[str]    		=scale_embedding  # scale factor will be sqrt(d_model) if True
										lowercase :							str    		=max_target_positions

										super().__init__(
										    pad_token_id=UpperCAmelCase__		,					bos_token_id=UpperCAmelCase__		,					eos_token_id=UpperCAmelCase__		,					decoder_start_token_id=UpperCAmelCase__		,					**UpperCAmelCase__		,					)





