

from __future__ import annotations





def 	__a     (      A__			:  list			,  A__			:  int			,  A__			:  int			,  A__			:  int       ):
    SCREAMING_SNAKE_CASE										=   []
    SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   input_list[low:mid], input_list[mid : high + 1]
    while left and right:
        result.append((left if left[0] <= right[0] else right).pop(0       )       )
    SCREAMING_SNAKE_CASE										=   result + left + right
    return input_list





def 	__a     (      A__			:  list       ):
    if len(A__       ) <= 1:
        return input_list
    SCREAMING_SNAKE_CASE										=   list(A__       )

    # iteration for two-way merging
    SCREAMING_SNAKE_CASE										=   2
    while p <= len(A__       ):
        # getting low, high and middle value for merge-sort of single list
        for i in range(0			,  len(A__       )			,  A__       ):
            SCREAMING_SNAKE_CASE										=   i
            SCREAMING_SNAKE_CASE										=   i + p - 1
            SCREAMING_SNAKE_CASE										=   (low + high + 1) // 2
            SCREAMING_SNAKE_CASE										=   merge(A__			,  A__			,  A__			,  A__       )
        # final merge of last two parts
        if p * 2 >= len(A__       ):
            SCREAMING_SNAKE_CASE										=   i
            SCREAMING_SNAKE_CASE										=   merge(A__			,  0			,  A__			,  len(A__       ) - 1       )
            break
        p *= 2

    return input_list


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

'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging


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

lowerCAmelCase					:    Dict           = {
    '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 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							"""mctct"""







				def __init__(       self						,				A_=8065						,				A_=1536						,				A_=36						,				A_=6144						,				A_=4						,				A_=384						,				A_=920						,				A_=1e-5						,				A_=0.3						,				A_="relu"						,				A_=0.02						,				A_=0.3						,				A_=0.3						,				A_=1						,				A_=0						,				A_=2						,				A_=1						,				A_=0.3						,				A_=1						,				A_=(7,)						,				A_=(3,)						,				A_=80						,				A_=1						,				A_=None						,				A_="sum"						,				A_=False						,				**A_						,				)->		str:







											'''simple docstring'''






											super().__init__(**A_						,				pad_token_id=A_						,				bos_token_id=A_						,				eos_token_id=A_     )
											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(A_     )
											UpperCamelCase   			=     list(A_     )

											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}`.'''     )




