




import math




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_ = 0					,     lowercase_ = 0      )       ->	list:

    """simple docstring"""


    __UpperCamelCase  		=						end or len(lowercase_      )
    for i in range(lowercase_					,     lowercase_      ):
        __UpperCamelCase  		=						i
        __UpperCamelCase  		=						array[i]
        while temp_index != start and temp_index_value < array[temp_index - 1]:
            __UpperCamelCase  		=						array[temp_index - 1]
            temp_index -= 1
        __UpperCamelCase  		=						temp_index_value
    return array




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_      )       ->	None:  # Max Heap

    """simple docstring"""


    __UpperCamelCase  		=						index
    __UpperCamelCase  		=						2 * index + 1  # Left Node
    __UpperCamelCase  		=						2 * index + 2  # Right Node

    if left_index < heap_size and array[largest] < array[left_index]:
        __UpperCamelCase  		=						left_index

    if right_index < heap_size and array[largest] < array[right_index]:
        __UpperCamelCase  		=						right_index

    if largest != index:
        __UpperCamelCase  		=						array[largest], array[index]
        heapify(lowercase_					,     lowercase_					,     lowercase_      )




def 					__SCREAMING_SNAKE_CASE   (  lowercase_      )       ->	list:

    """simple docstring"""


    __UpperCamelCase  		=						len(lowercase_      )

    for i in range(n // 2					,     -1					,     -1      ):
        heapify(lowercase_					,     lowercase_					,     lowercase_      )

    for i in range(n - 1					,     0					,     -1      ):
        __UpperCamelCase  		=						array[0], array[i]
        heapify(lowercase_					,     0					,     lowercase_      )

    return array




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )       ->	int:

    """simple docstring"""


    if (array[first_index] > array[middle_index]) != (
        array[first_index] > array[last_index]
    ):
        return array[first_index]
    elif (array[middle_index] > array[first_index]) != (
        array[middle_index] > array[last_index]
    ):
        return array[middle_index]
    else:
        return array[last_index]




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )       ->	int:

    """simple docstring"""


    __UpperCamelCase  		=						low
    __UpperCamelCase  		=						high
    while True:
        while array[i] < pivot:
            i += 1
        j -= 1
        while pivot < array[j]:
            j -= 1
        if i >= j:
            return i
        __UpperCamelCase  		=						array[j], array[i]
        i += 1




def 					__SCREAMING_SNAKE_CASE   (  lowercase_      )       ->	list:

    """simple docstring"""


    if len(lowercase_      ) == 0:
        return array
    __UpperCamelCase  		=						2 * math.ceil(math.loga(len(lowercase_      )      )      )
    __UpperCamelCase  		=						16
    return intro_sort(lowercase_					,     0					,     len(lowercase_      )					,     lowercase_					,     lowercase_      )




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )       ->	list:

    """simple docstring"""


    while end - start > size_threshold:
        if max_depth == 0:
            return heap_sort(lowercase_      )
        max_depth -= 1
        __UpperCamelCase  		=						median_of_a(lowercase_					,     lowercase_					,     start + ((end - start) // 2) + 1					,     end - 1      )
        __UpperCamelCase  		=						partition(lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )
        intro_sort(lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )
        __UpperCamelCase  		=						p
    return insertion_sort(lowercase_					,     lowercase_					,     lowercase_      )


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 a_   		=     input("Enter numbers separated by a comma : ").strip()
 a_   		=     [float(item) for item in user_input.split(",")]
 print(sort(unsorted))








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


a_   		=     logging.get_logger(__name__)

a_   		=     {
    "speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}

class  _lowerCamelCase						(			_SCREAMING_SNAKE_CASE   ):

      """simple docstring"""

      lowerCAmelCase__			: int    =					"mctct"







      def __init__(     self					: List[Any] ,       snake_case					: Optional[Any]=8065 ,       snake_case					: Optional[int]=1536 ,       snake_case					: Any=36 ,       snake_case					: List[str]=6144 ,       snake_case					: Dict=4 ,       snake_case					: str=384 ,       snake_case					: List[str]=920 ,       snake_case					: Dict=1E-5 ,       snake_case					: Union[str, Any]=0.3 ,       snake_case					: Optional[Any]="relu" ,       snake_case					: str=0.02 ,       snake_case					: Optional[int]=0.3 ,       snake_case					: int=0.3 ,       snake_case					: Any=1 ,       snake_case					: int=0 ,       snake_case					: Union[str, Any]=2 ,       snake_case					: List[Any]=1 ,       snake_case					: Dict=0.3 ,       snake_case					: int=1 ,       snake_case					: Optional[int]=(7,) ,       snake_case					: List[Any]=(3,) ,       snake_case					: Optional[int]=80 ,       snake_case					: List[str]=1 ,       snake_case					: int=None ,       snake_case					: List[str]="sum" ,       snake_case					: Tuple=False ,       **snake_case					: List[str] ,       ):
          super().__init__(**snake_case ,       pad_token_id=snake_case ,       bos_token_id=snake_case ,       eos_token_id=snake_case				)
          __UpperCamelCase  		=						vocab_size
          __UpperCamelCase  		=						hidden_size
          __UpperCamelCase  		=						num_hidden_layers
          __UpperCamelCase  		=						intermediate_size
          __UpperCamelCase  		=						num_attention_heads
          __UpperCamelCase  		=						attention_head_dim
          __UpperCamelCase  		=						max_position_embeddings
          __UpperCamelCase  		=						layer_norm_eps
          __UpperCamelCase  		=						layerdrop
          __UpperCamelCase  		=						hidden_act
          __UpperCamelCase  		=						initializer_range
          __UpperCamelCase  		=						hidden_dropout_prob
          __UpperCamelCase  		=						attention_probs_dropout_prob
          __UpperCamelCase  		=						pad_token_id
          __UpperCamelCase  		=						bos_token_id
          __UpperCamelCase  		=						eos_token_id
          __UpperCamelCase  		=						conv_glu_dim
          __UpperCamelCase  		=						conv_dropout
          __UpperCamelCase  		=						num_conv_layers
          __UpperCamelCase  		=						input_feat_per_channel
          __UpperCamelCase  		=						input_channels
          __UpperCamelCase  		=						conv_channels
          __UpperCamelCase  		=						ctc_loss_reduction
          __UpperCamelCase  		=						ctc_zero_infinity

          # prevents config testing fail with exporting to json
          __UpperCamelCase  		=						list(snake_case				)
          __UpperCamelCase  		=						list(snake_case				)

          if len(self.conv_kernel				) != self.num_conv_layers:
              raise ValueError(
                  '''Configuration for convolutional module is incorrect. '''
                  '''It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '''
                  F"but is `len(config.conv_kernel) = {len(self.conv_kernel				)}`, "
                  F"`config.num_conv_layers = {self.num_conv_layers}`."				)






