
"""simple docstring"""

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


_lowerCamelCase  :			Optional[Any]        =       logging.get_logger(__name__)

_lowerCamelCase  :			Dict        =       {
    '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        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Any         =   """speech_to_text_2"""
				__lowerCAmelCase    :    Any         =   ["""past_key_values"""]
				__lowerCAmelCase    :    int         =   {"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}







				def __init__(							self   :					str      ,     _lowerCamelCase   :					Tuple=1_00_00      ,     _lowerCamelCase   :					Any=6      ,     _lowerCamelCase   :					Tuple=20_48      ,     _lowerCamelCase   :					List[Any]=4      ,     _lowerCamelCase   :					str=0.0      ,     _lowerCamelCase   :					List[Any]=True      ,     _lowerCamelCase   :					Any="relu"      ,     _lowerCamelCase   :					Union[str, Any]=2_56      ,     _lowerCamelCase   :					Optional[int]=0.1      ,     _lowerCamelCase   :					int=0.0      ,     _lowerCamelCase   :					Tuple=0.0      ,     _lowerCamelCase   :					Union[str, Any]=0.02      ,     _lowerCamelCase   :					List[Any]=2      ,     _lowerCamelCase   :					Any=True      ,     _lowerCamelCase   :					Tuple=1      ,     _lowerCamelCase   :					str=0      ,     _lowerCamelCase   :					Any=2      ,     _lowerCamelCase   :					Dict=10_24      ,     **_lowerCamelCase   :					str      ,     ):



					"""simple docstring"""

					A_  :				Dict	   =		vocab_size
					A_  :				Optional[int]	   =		d_model
					A_  :				Dict	   =		decoder_ffn_dim
					A_  :				Tuple	   =		decoder_layers
					A_  :				List[str]	   =		decoder_attention_heads
					A_  :				Optional[int]	   =		dropout
					A_  :				Tuple	   =		attention_dropout
					A_  :				List[str]	   =		activation_dropout
					A_  :				List[Any]	   =		activation_function
					A_  :				List[Any]	   =		init_std
					A_  :				Tuple	   =		decoder_layerdrop
					A_  :				Optional[Any]	   =		use_cache
					A_  :				int	   =		decoder_layers
					A_  :				Any	   =		scale_embedding  # scale factor will be sqrt(d_model) if True
					A_  :				Dict	   =		max_target_positions

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











"""simple docstring"""

def 		lowercase_      (		_UpperCAmelCase	):




	"""simple docstring"""






	A_  :				int	   =		len(_UpperCAmelCase	)
	for i in range(length - 1	):
		A_  :				str	   =		i
		for k in range(i + 1  ,      _UpperCAmelCase	):
			if collection[k] < collection[least]:
				A_  :				Tuple	   =		k
		if least != i:
			A_   , A_  :				Optional[int]	   =		(collection[i], collection[least])
	return collection


if __name__ == "__main__":
		_lowerCamelCase  :			Optional[int]        =       input('Enter numbers separated by a comma:\n').strip()
		_lowerCamelCase  :			List[str]        =       [int(item) for item in user_input.split(',')]
		print(selection_sort(unsorted))





