


def 				lowerCamelCase__	(      a	:   Optional[Any]				)    ->	str:





			"""simple docstring"""
			# if the collection is empty, returns empty
			if collection == []:
						return []

			# get some information about the collection
			a__ :Tuple						  =    len(a				)
			a__ :Optional[Any]						  =    max(a				)
			a__ :int						  =    min(a				)

			# create the counting array
			a__ :List[Any]						  =    coll_max + 1 - coll_min
			a__ :Union[str, Any]						  =    [0] * counting_arr_length

			# count how much a number appears in the collection
			for number in collection:
						counting_arr[number - coll_min] += 1

			# sum each position with it's predecessors. now, counting_arr[i] tells
			# us how many elements <= i has in the collection
			for i in range(1	,  a				):
						a__ :Any						  =    counting_arr[i] + counting_arr[i - 1]

			# create the output collection
			a__ :str						  =    [0] * coll_len

			# place the elements in the output, respecting the original order (stable
			# sort) from end to begin, updating counting_arr
			for i in reversed(range(0	,  a				)				):
						a__ :Optional[Any]						  =    collection[i]
						counting_arr[collection[i] - coll_min] -= 1

			return ordered


def 				lowerCamelCase__	(      a	:   int				)    ->	Optional[Any]:





			"""simple docstring"""
			return "".join([chr(a				) for i in counting_sort([ord(a				) for c in string]				)]				)


if __name__ == "__main__":
		# Test string sort
		assert counting_sort_string('''thisisthestring''') == "eghhiiinrsssttt"

		snake_case__						 =						input('''Enter numbers separated by a comma:\n''').strip()
		snake_case__						 =						[int(item) for item in user_input.split(''',''')]
		print(counting_sort(unsorted))






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


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''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 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     'speech_to_text_2'
						lowerCamelCase_         =     ['past_key_values']
						lowerCamelCase_         =     {'num_attention_heads': 'decoder_attention_heads', 'hidden_size': 'd_model'}




						def __init__(	self						:   Dict   ,     __A						:   Union[str, Any]=10000   ,     __A						:   Tuple=6   ,     __A						:   Tuple=2048   ,     __A						:   Any=4   ,     __A						:   str=0.0   ,     __A						:   Tuple=True   ,     __A						:   List[Any]="relu"   ,     __A						:   Union[str, Any]=256   ,     __A						:   str=0.1   ,     __A						:   Optional[Any]=0.0   ,     __A						:   Tuple=0.0   ,     __A						:   Any=0.02   ,     __A						:   int=2   ,     __A						:   Union[str, Any]=True   ,     __A						:   Tuple=1   ,     __A						:   List[str]=0   ,     __A						:   List[str]=2   ,     __A						:   Union[str, Any]=1024   ,     **__A						:   Tuple   ,     )      ->List[str]:






									"""simple docstring"""






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

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


