






import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow


@require_torch
class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    int:
					snake_case__      :Optional[Any]         =   "ylacombe/bark-small"
					snake_case__      :Dict         =   tempfile.mkdtemp()
					snake_case__      :Tuple         =   "en_speaker_1"
					snake_case__      :List[Any]         =   "This is a test string"
					snake_case__      :List[Any]         =   "speaker_embeddings_path.json"
					snake_case__      :Optional[Any]         =   "speaker_embeddings"






	def    lowerCAmelCase_							(		self					,**UpperCamelCase       )						->    Union[str, Any]:
					return AutoTokenizer.from_pretrained(self.checkpoint					,**UpperCamelCase       )






	def    lowerCAmelCase_							(		self       )						->    Dict:
					shutil.rmtree(self.tmpdirname       )






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					snake_case__      :List[str]         =   self.get_tokenizer()

					snake_case__      :Tuple         =   BarkProcessor(tokenizer=UpperCamelCase       )

					processor.save_pretrained(self.tmpdirname       )
					snake_case__      :Tuple         =   BarkProcessor.from_pretrained(self.tmpdirname       )

					self.assertEqual(processor.tokenizer.get_vocab()					,tokenizer.get_vocab()       )






	@slow
	def    lowerCAmelCase_							(		self       )						->    Any:
					snake_case__      :List[str]         =   BarkProcessor.from_pretrained(
					    pretrained_processor_name_or_path=self.checkpoint					,speaker_embeddings_dict_path=self.speaker_embeddings_dict_path					,)
					processor.save_pretrained(
					    self.tmpdirname					,speaker_embeddings_dict_path=self.speaker_embeddings_dict_path					,speaker_embeddings_directory=self.speaker_embeddings_directory					,)

					snake_case__      :Tuple         =   self.get_tokenizer(bos_token="(BOS)"					,eos_token="(EOS)"       )

					snake_case__      :int         =   BarkProcessor.from_pretrained(
					    self.tmpdirname					,self.speaker_embeddings_dict_path					,bos_token="(BOS)"					,eos_token="(EOS)"					,)

					self.assertEqual(processor.tokenizer.get_vocab()					,tokenizer_add_kwargs.get_vocab()       )






	def    lowerCAmelCase_							(		self       )						->    Any:
					snake_case__      :List[Any]         =   BarkProcessor.from_pretrained(
					    pretrained_processor_name_or_path=self.checkpoint					,speaker_embeddings_dict_path=self.speaker_embeddings_dict_path					,)

					snake_case__      :Optional[Any]         =   35
					snake_case__      :Optional[int]         =   2
					snake_case__      :str         =   8

					snake_case__      :Any         =   {
					    "semantic_prompt": np.ones(UpperCamelCase       ),
					    "coarse_prompt": np.ones((nb_codebooks_coarse, seq_len)       ),
					    "fine_prompt": np.ones((nb_codebooks_total, seq_len)       ),
					}

					# test providing already loaded voice_preset
					snake_case__      :Any         =   processor(text=self.input_string					,voice_preset=UpperCamelCase       )

					snake_case__      :List[str]         =   inputs["history_prompt"]
					for key in voice_preset:
									self.assertListEqual(voice_preset[key].tolist()					,processed_voice_preset.get(UpperCamelCase					,np.array([]       )       ).tolist()       )

					# test loading voice preset from npz file
					snake_case__      :List[str]         =   os.path.join(self.tmpdirname					,"file.npz"       )
					np.savez(UpperCamelCase					,**UpperCamelCase       )
					snake_case__      :Union[str, Any]         =   processor(text=self.input_string					,voice_preset=UpperCamelCase       )
					snake_case__      :int         =   inputs["history_prompt"]

					for key in voice_preset:
									self.assertListEqual(voice_preset[key].tolist()					,processed_voice_preset.get(UpperCamelCase					,np.array([]       )       ).tolist()       )

					# test loading voice preset from the hub
					snake_case__      :Dict         =   processor(text=self.input_string					,voice_preset=self.voice_preset       )






	def    lowerCAmelCase_							(		self       )						->    str:
					snake_case__      :int         =   self.get_tokenizer()

					snake_case__      :str         =   BarkProcessor(tokenizer=UpperCamelCase       )

					snake_case__      :List[Any]         =   processor(text=self.input_string       )

					snake_case__      :Optional[int]         =   tokenizer(
					    self.input_string					,padding="max_length"					,max_length=256					,add_special_tokens=UpperCamelCase					,return_attention_mask=UpperCamelCase					,return_token_type_ids=UpperCamelCase					,)

					for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key]					,encoded_processor[key].squeeze().tolist()       )







def 					lowercase_ (    __snake_case     :							str      )     -> list:





				'''simple docstring'''


				return [
				    txt[:a] + txt[a].upper() + txt[a + 1 :]
				    for a in range(len(__snake_case      )      )
				    if txt[a].isalpha()
				]


if __name__ == "__main__":
	__import__("doctest").testmod()