



"""simple docstring"""
import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE     :  Tuple										=					logging.get_logger(__name__)


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					lowercase__      :				Any        =       'semantic'

					def __init__(			self ,				lowerCamelCase__=1_0_0_0_0 ,				lowerCamelCase__=True ,				lowerCamelCase__=7_6_8 ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=0.7 ,				lowerCamelCase__=True ,				lowerCamelCase__=1_0_0_4_8 ,				lowerCamelCase__=1_2_9_5_9_5 ,				lowerCamelCase__=1_2_9_5_9_9 ,				lowerCamelCase__=1_0_0_0_0 ,				lowerCamelCase__=2_5_6 ,				lowerCamelCase__=4_9.9 ,				**lowerCamelCase__ ,				):
									super().__init__(
									    temperature=lowerCamelCase__ ,				do_sample=lowerCamelCase__ ,				eos_token_id=lowerCamelCase__ ,				renormalize_logits=lowerCamelCase__ ,				max_new_tokens=lowerCamelCase__ ,				output_scores=lowerCamelCase__ ,				return_dict_in_generate=lowerCamelCase__ ,				output_hidden_states=lowerCamelCase__ ,				output_attentions=lowerCamelCase__ ,				**lowerCamelCase__ ,				)

									_lowerCamelCase					     = text_encoding_offset
									_lowerCamelCase					     = text_pad_token
									_lowerCamelCase					     = eos_token_id
									_lowerCamelCase					     = semantic_infer_token
									_lowerCamelCase					     = semantic_vocab_size
									_lowerCamelCase					     = max_input_semantic_length
									_lowerCamelCase					     = semantic_rate_hz


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					lowercase__      :				str        =       'coarse_acoustics'

					def __init__(			self ,				lowerCamelCase__=True ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=False ,				lowerCamelCase__=0.7 ,				lowerCamelCase__=True ,				lowerCamelCase__=1_2_0_4_8 ,				lowerCamelCase__=7_5 ,				lowerCamelCase__=2 ,				lowerCamelCase__=1_2_0_5_0 ,				lowerCamelCase__=2_5_6 ,				lowerCamelCase__ = 6_3_0 ,				lowerCamelCase__ = 6_0 ,				**lowerCamelCase__ ,				):
									super().__init__(
									    temperature=lowerCamelCase__ ,				do_sample=lowerCamelCase__ ,				renormalize_logits=lowerCamelCase__ ,				output_scores=lowerCamelCase__ ,				return_dict_in_generate=lowerCamelCase__ ,				output_hidden_states=lowerCamelCase__ ,				output_attentions=lowerCamelCase__ ,				**lowerCamelCase__ ,				)

									_lowerCamelCase					     = coarse_semantic_pad_token
									_lowerCamelCase					     = coarse_rate_hz
									_lowerCamelCase					     = n_coarse_codebooks
									_lowerCamelCase					     = coarse_infer_token
									_lowerCamelCase					     = max_coarse_input_length
									_lowerCamelCase					     = max_coarse_history
									_lowerCamelCase					     = sliding_window_len


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					lowercase__      :				Tuple        =       'fine_acoustics'

					def __init__(			self ,				lowerCamelCase__=0.5 ,				lowerCamelCase__=5_1_2 ,				lowerCamelCase__=1_0_2_4 ,				lowerCamelCase__=8 ,				**lowerCamelCase__ ,				):
									super().__init__(temperature=lowerCamelCase__      )

									_lowerCamelCase					     = max_fine_history_length
									_lowerCamelCase					     = max_fine_input_length
									_lowerCamelCase					     = n_fine_codebooks


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					lowercase__      :				int        =       'bark'
					lowercase__      :				str        =       True

					def __init__(			self ,				lowerCamelCase__ = None ,				lowerCamelCase__ = None ,				lowerCamelCase__ = None ,				lowerCamelCase__=2_4_0_0_0 ,				lowerCamelCase__=1_0_2_4 ,				**lowerCamelCase__ ,				):
									if semantic_config is None:
													_lowerCamelCase					     = {}
													logger.info('''semantic_config is None. initializing the semantic model with default values.'''      )

									if coarse_acoustics_config is None:
													_lowerCamelCase					     = {}
													logger.info('''coarse_acoustics_config is None. initializing the coarse model with default values.'''      )

									if fine_acoustics_config is None:
													_lowerCamelCase					     = {}
													logger.info('''fine_acoustics_config is None. initializing the fine model with default values.'''      )

									_lowerCamelCase					     = BarkSemanticGenerationConfig(**lowerCamelCase__      )
									_lowerCamelCase					     = BarkCoarseGenerationConfig(**lowerCamelCase__      )
									_lowerCamelCase					     = BarkFineGenerationConfig(**lowerCamelCase__      )

									_lowerCamelCase					     = sample_rate
									_lowerCamelCase					     = codebook_size

					@classmethod
					def 	snake_case__					(			cls ,				lowerCamelCase__ ,				lowerCamelCase__ ,				lowerCamelCase__ ,				**lowerCamelCase__ ,				):
									return cls(
									    semantic_config=semantic_config.to_dict() ,				coarse_acoustics_config=coarse_acoustics_config.to_dict() ,				fine_acoustics_config=fine_acoustics_config.to_dict() ,				**lowerCamelCase__ ,				)





					def 	snake_case__					(			self      ):
									_lowerCamelCase					     = copy.deepcopy(self.__dict__      )

									_lowerCamelCase					     = self.semantic_config.to_dict()
									_lowerCamelCase					     = self.coarse_acoustics_config.to_dict()
									_lowerCamelCase					     = self.fine_acoustics_config.to_dict()

									_lowerCamelCase					     = self.__class__.model_type
									return output





"""simple docstring"""
def 				lowerCAmelCase_(      lowercase_   :							str  ,      lowercase_   :							str							)		->				int:
				# The longer word should come first
				if len(lowercase_							) < len(lowercase_							):
								return levenshtein_distance(lowercase_  ,      lowercase_							)

				if len(lowercase_							) == 0:
								return len(lowercase_							)

				_lowerCamelCase					     = list(range(len(lowercase_							) + 1							)							)

				for i, ca in enumerate(lowercase_							):
								_lowerCamelCase					     = [i + 1]

								for j, ca in enumerate(lowercase_							):
												# Calculate insertions, deletions and substitutions
												_lowerCamelCase					     = previous_row[j + 1] + 1
												_lowerCamelCase					     = current_row[j] + 1
												_lowerCamelCase					     = previous_row[j] + (ca != ca)

												# Get the minimum to append to the current row
												current_row.append(min(lowercase_  ,      lowercase_  ,      lowercase_							)							)

								# Store the previous row
								_lowerCamelCase					     = current_row

				# Returns the last element (distance)
				return previous_row[-1]


if __name__ == "__main__":
			__SCREAMING_SNAKE_CASE     :  int										=					input('''Enter the first word:\n''').strip()
			__SCREAMING_SNAKE_CASE     :  Optional[Any]										=					input('''Enter the second word:\n''').strip()

			__SCREAMING_SNAKE_CASE     :  Optional[Any]										=					levenshtein_distance(first_word, second_word)
			print(F"""Levenshtein distance between {first_word} and {second_word} is {result}""")
