


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a : Any		=				logging.get_logger(__name__)

a : Any		=				{'''vocab_file''': '''spm_char.model'''}

a : Optional[Any]		=				{
    '''vocab_file''': {
        '''microsoft/speecht5_asr''': '''https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model''',
        '''microsoft/speecht5_tts''': '''https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model''',
        '''microsoft/speecht5_vc''': '''https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model''',
    }
}

a : int		=				{
    '''microsoft/speecht5_asr''': 1024,
    '''microsoft/speecht5_tts''': 1024,
    '''microsoft/speecht5_vc''': 1024,
}
class 	lowerCamelCase_       (				lowerCAmelCase__				):



					'''simple docstring'''







					__UpperCAmelCase            =				VOCAB_FILES_NAMES
					__UpperCAmelCase            =				PRETRAINED_VOCAB_FILES_MAP
					__UpperCAmelCase            =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__UpperCAmelCase            =				["input_ids", "attention_mask"]






					def __init__(				self ,       snake_case_ ,       snake_case_="<s>" ,       snake_case_="</s>" ,       snake_case_="<unk>" ,       snake_case_="<pad>" ,       snake_case_ = None ,       **snake_case_ ,       )   ->			None:







								'''simple docstring'''

								__lowercase 					=   {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=snake_case_ ,       eos_token=snake_case_ ,       unk_token=snake_case_ ,       pad_token=snake_case_ ,       sp_model_kwargs=self.sp_model_kwargs ,       **snake_case_ ,       )

								__lowercase 					=   vocab_file

								__lowercase 					=   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(snake_case_						)






					@property
					def A      (				self						)   ->			Any:







								'''simple docstring'''

								return self.sp_model.get_piece_size()






					def A      (				self						)   ->			Union[str, Any]:







								'''simple docstring'''

								__lowercase 					=   {self.convert_ids_to_tokens(snake_case_						): i for i in range(self.vocab_size						)}
								vocab.update(self.added_tokens_encoder						)
								return vocab






					def __getstate__(				self						)   ->			List[str]:







								'''simple docstring'''

								__lowercase 					=   self.__dict__.copy()
								__lowercase 					=   None
								return state






					def __setstate__(				self ,       snake_case_						)   ->			int:







								'''simple docstring'''

								__lowercase 					=   d

								# for backward compatibility
								if not hasattr(self ,       '''sp_model_kwargs'''						):
											__lowercase 					=   {}

								__lowercase 					=   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(self.vocab_file						)






					def A      (				self ,       snake_case_						)   ->			List[str]:







								'''simple docstring'''

								return self.sp_model.encode(snake_case_ ,       out_type=snake_case_						)






					def A      (				self ,       snake_case_						)   ->			Tuple:







								'''simple docstring'''

								return self.sp_model.piece_to_id(snake_case_						)






					def A      (				self ,       snake_case_						)   ->			Tuple:







								'''simple docstring'''

								__lowercase 					=   self.sp_model.IdToPiece(snake_case_						)
								return token






					def A      (				self ,       snake_case_						)   ->			Optional[Any]:







								'''simple docstring'''

								__lowercase 					=   []
								__lowercase 					=   ''''''
								for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
														out_string += self.sp_model.decode(snake_case_						) + token
														__lowercase 					=   []
											else:
														current_sub_tokens.append(snake_case_						)
								out_string += self.sp_model.decode(snake_case_						)
								return out_string.strip()






					def A      (				self ,       snake_case_ ,       snake_case_=None						)   ->			List[int]:







								'''simple docstring'''

								if token_ids_a is None:
											return token_ids_a + [self.eos_token_id]
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return token_ids_a + token_ids_a + [self.eos_token_id]






					def A      (				self ,       snake_case_ ,       snake_case_ = None ,       snake_case_ = False						)   ->			List[int]:







								'''simple docstring'''

								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=snake_case_ ,       token_ids_a=snake_case_ ,       already_has_special_tokens=snake_case_						)

								__lowercase 					=   [1]
								if token_ids_a is None:
											return ([0] * len(snake_case_						)) + suffix_ones
								return ([0] * len(snake_case_						)) + ([0] * len(snake_case_						)) + suffix_ones






					def A      (				self ,       snake_case_ ,       snake_case_ = None						)   ->			Tuple[str]:







								'''simple docstring'''

								if not os.path.isdir(snake_case_						):
											logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
											return
								__lowercase 					=   os.path.join(
								    snake_case_ ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

								if os.path.abspath(self.vocab_file						) != os.path.abspath(snake_case_						) and os.path.isfile(self.vocab_file						):
											copyfile(self.vocab_file ,       snake_case_						)
								elif not os.path.isfile(self.vocab_file						):
											with open(snake_case_ ,       '''wb'''						) as fi:
														__lowercase 					=   self.sp_model.serialized_model_proto()
														fi.write(snake_case_						)

								return (out_vocab_file,)






import unittest

from knapsack import knapsack as k
class 	lowerCamelCase_       (				unittest.TestCase				):



					'''simple docstring'''







					def A      (				self						)   ->			Optional[Any]:







								'''simple docstring'''

								__lowercase 					=   0
								__lowercase 					=   [0]
								__lowercase 					=   [0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)

								__lowercase 					=   [6_0]
								__lowercase 					=   [1_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)






					def A      (				self						)   ->			Tuple:







								'''simple docstring'''

								__lowercase 					=   3
								__lowercase 					=   [1, 2, 3]
								__lowercase 					=   [3, 2, 1]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       5						)






					def A      (				self						)   ->			str:







								'''simple docstring'''

								__lowercase 					=   5_0
								__lowercase 					=   [6_0, 1_0_0, 1_2_0]
								__lowercase 					=   [1_0, 2_0, 3_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       2_2_0						)


if __name__ == "__main__":
	unittest.main()


