"""simple docstring"""







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  UpperCamelCase	(    unittest.TestCase						):
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			'''ylacombe/bark-small'''
        lowercase_			:       Dict									=			tempfile.mkdtemp()
        lowercase_			:       Dict									=			'''en_speaker_1'''
        lowercase_			:       Optional[int]									=			'''This is a test string'''
        lowercase_			:       Union[str, Any]									=			'''speaker_embeddings_path.json'''
        lowercase_			:       str									=			'''speaker_embeddings'''
   def     _UpperCAmelCase     (    self  ,**__UpperCamelCase    )			->   Optional[Any]:


        '''simple docstring'''


        return AutoTokenizer.from_pretrained(self.checkpoint  ,**lowerCamelCase__    )
   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        shutil.rmtree(self.tmpdirname    )
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       List[str]									=			self.get_tokenizer()

        lowercase_			:       str									=			BarkProcessor(tokenizer=lowerCamelCase__    )

        processor.save_pretrained(self.tmpdirname    )
        lowercase_			:       Optional[Any]									=			BarkProcessor.from_pretrained(self.tmpdirname    )

        self.assertEqual(processor.tokenizer.get_vocab()  ,tokenizer.get_vocab()    )
   @slow
   def     _UpperCAmelCase     (    self    )			->   Optional[Any]:


        '''simple docstring'''


        lowercase_			:       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  ,)

        lowercase_			:       Union[str, Any]									=			self.get_tokenizer(bos_token='(BOS)'  ,eos_token='(EOS)'    )

        lowercase_			:       Union[str, Any]									=			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     _UpperCAmelCase     (    self    )			->   int:


        '''simple docstring'''


        lowercase_			:       int									=			BarkProcessor.from_pretrained(
            pretrained_processor_name_or_path=self.checkpoint  ,speaker_embeddings_dict_path=self.speaker_embeddings_dict_path  ,)

        lowercase_			:       str									=			35
        lowercase_			:       int									=			2
        lowercase_			:       List[Any]									=			8

        lowercase_			:       str									=			{
            '''semantic_prompt''': np.ones(lowerCamelCase__    ),
            '''coarse_prompt''': np.ones((nb_codebooks_coarse, seq_len)    ),
            '''fine_prompt''': np.ones((nb_codebooks_total, seq_len)    ),
        }

        # test providing already loaded voice_preset
        lowercase_			:       int									=			processor(text=self.input_string  ,voice_preset=lowerCamelCase__    )

        lowercase_			:       Dict									=			inputs['''history_prompt''']
        for key in voice_preset:
             self.assertListEqual(voice_preset[key].tolist()  ,processed_voice_preset.get(lowerCamelCase__  ,np.array([]    )    ).tolist()    )

        # test loading voice preset from npz file
        lowercase_			:       Tuple									=			os.path.join(self.tmpdirname  ,'file.npz'    )
        np.savez(lowerCamelCase__  ,**lowerCamelCase__    )
        lowercase_			:       Dict									=			processor(text=self.input_string  ,voice_preset=lowerCamelCase__    )
        lowercase_			:       Optional[Any]									=			inputs['''history_prompt''']

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

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







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


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			self.get_tokenizer()

        lowercase_			:       Tuple									=			BarkProcessor(tokenizer=lowerCamelCase__    )

        lowercase_			:       List[str]									=			processor(text=self.input_string    )

        lowercase_			:       str									=			tokenizer(
            self.input_string  ,padding='max_length'  ,max_length=256  ,add_special_tokens=lowerCamelCase__  ,return_attention_mask=lowerCamelCase__  ,return_token_type_ids=lowerCamelCase__  ,)

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


"""simple docstring"""







from diffusers.utils.testing_utils import require_onnxruntime







@require_onnxruntime
class  UpperCamelCase	:
   pass

