
'''simple docstring'''



import functools
import operator

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


__A       =      logging.get_logger(__name__)

__A       =      {
    "facebook/hubert-base-ls960": "https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json",
    # See all Hubert models at https://huggingface.co/models?filter=hubert
}





class      A							(    __UpperCAmelCase			):
			lowerCamelCase							:							List[Any]    						=					"""hubert"""



			def __init__(   self    ,       lowerCamelCase__=32    ,       lowerCamelCase__=768    ,       lowerCamelCase__=12    ,       lowerCamelCase__=12    ,       lowerCamelCase__=3_072    ,       lowerCamelCase__="gelu"    ,       lowerCamelCase__=0.1    ,       lowerCamelCase__=0.1    ,       lowerCamelCase__=0.1    ,       lowerCamelCase__=True    ,       lowerCamelCase__=0.0    ,       lowerCamelCase__=0.1    ,       lowerCamelCase__=0.1    ,       lowerCamelCase__=0.02    ,       lowerCamelCase__=1e-5    ,       lowerCamelCase__="group"    ,       lowerCamelCase__="gelu"    ,       lowerCamelCase__=(512, 512, 512, 512, 512, 512, 512)    ,       lowerCamelCase__=(5, 2, 2, 2, 2, 2, 2)    ,       lowerCamelCase__=(10, 3, 3, 3, 3, 2, 2)    ,       lowerCamelCase__=False    ,       lowerCamelCase__=128    ,       lowerCamelCase__=16    ,       lowerCamelCase__=False    ,       lowerCamelCase__=True    ,       lowerCamelCase__=0.05    ,       lowerCamelCase__=10    ,       lowerCamelCase__=2    ,       lowerCamelCase__=0.0    ,       lowerCamelCase__=10    ,       lowerCamelCase__=0    ,       lowerCamelCase__="sum"    ,       lowerCamelCase__=False    ,       lowerCamelCase__=False    ,       lowerCamelCase__=256    ,       lowerCamelCase__=0    ,       lowerCamelCase__=1    ,       lowerCamelCase__=2    ,       **lowerCamelCase__    ,       )     ->						Tuple:




									'''simple docstring'''



									super().__init__(**lowerCamelCase__    ,       pad_token_id=lowerCamelCase__    ,       bos_token_id=lowerCamelCase__    ,       eos_token_id=lowerCamelCase__    )
									lowercase__								=    hidden_size
									lowercase__								=    feat_extract_norm
									lowercase__								=    feat_extract_activation
									lowercase__								=    list(lowerCamelCase__    )
									lowercase__								=    list(lowerCamelCase__    )
									lowercase__								=    list(lowerCamelCase__    )
									lowercase__								=    conv_bias
									lowercase__								=    num_conv_pos_embeddings
									lowercase__								=    num_conv_pos_embedding_groups
									lowercase__								=    len(self.conv_dim    )
									lowercase__								=    num_hidden_layers
									lowercase__								=    intermediate_size
									lowercase__								=    hidden_act
									lowercase__								=    num_attention_heads
									lowercase__								=    hidden_dropout
									lowercase__								=    attention_dropout
									lowercase__								=    activation_dropout
									lowercase__								=    feat_proj_layer_norm
									lowercase__								=    feat_proj_dropout
									lowercase__								=    final_dropout
									lowercase__								=    layerdrop
									lowercase__								=    layer_norm_eps
									lowercase__								=    initializer_range
									lowercase__								=    vocab_size
									lowercase__								=    do_stable_layer_norm
									lowercase__								=    use_weighted_layer_sum
									lowercase__								=    classifier_proj_size

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

									# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
									lowercase__								=    apply_spec_augment
									lowercase__								=    mask_time_prob
									lowercase__								=    mask_time_length
									lowercase__								=    mask_time_min_masks
									lowercase__								=    mask_feature_prob
									lowercase__								=    mask_feature_length
									lowercase__								=    mask_feature_min_masks

									# ctc loss
									lowercase__								=    ctc_loss_reduction
									lowercase__								=    ctc_zero_infinity



			@property
			def A__	(   self    )     ->						Dict:




									'''simple docstring'''



									return functools.reduce(operator.mul    ,       self.conv_stride    ,       1    )








'''simple docstring'''



def 	_A						(							lowercase__						,						lowercase__						,						lowercase__		):
						if right <= left:
												return
						lowercase__								=    lowercase__								=    left
						lowercase__								=    right
						lowercase__								=    sorting[left]
						while i <= b:
												if sorting[i] < pivot:
																		lowercase__	,  lowercase__								=    sorting[i], sorting[a]
																		a += 1
																		i += 1
												elif sorting[i] > pivot:
																		lowercase__	,  lowercase__								=    sorting[i], sorting[b]
																		b -= 1
												else:
																		i += 1
						quick_sort_apartition(lowercase__						,						lowercase__						,						a - 1		)
						quick_sort_apartition(lowercase__						,						b + 1						,						lowercase__		)





def 	_A						(							lowercase__						,						lowercase__						,						lowercase__		):
						if left < right:
												lowercase__								=    lomuto_partition(lowercase__						,						lowercase__						,						lowercase__		)
												quick_sort_lomuto_partition(lowercase__						,						lowercase__						,						pivot_index - 1		)
												quick_sort_lomuto_partition(lowercase__						,						pivot_index + 1						,						lowercase__		)





def 	_A						(							lowercase__						,						lowercase__						,						lowercase__		):
						lowercase__								=    sorting[right]
						lowercase__								=    left
						for i in range(lowercase__						,						lowercase__		):
												if sorting[i] < pivot:
																		lowercase__	,  lowercase__								=    sorting[i], sorting[store_index]
																		store_index += 1
						lowercase__	,  lowercase__								=    sorting[store_index], sorting[right]
						return store_index





def 	_A						(							lowercase__		):
						if len(lowercase__		) <= 1:
												return sorting
						return (
						    three_way_radix_quicksort([i for i in sorting if i < sorting[0]]		)
						    + [i for i in sorting if i == sorting[0]]
						    + three_way_radix_quicksort([i for i in sorting if i > sorting[0]]		)
						)


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)

				__A       =      input("Enter numbers separated by a comma:\n").strip()
				__A       =      [int(item) for item in user_input.split(",")]
				quick_sort_apartition(unsorted, 0, len(unsorted) - 1)
				print(unsorted)






