



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  lowerCamelCase__	(    unittest.TestCase):
     """simple docstring"""



     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		"ylacombe/bark-small"
           lowerCamelCase             =		tempfile.mkdtemp()
           lowerCamelCase             =		"en_speaker_1"
           lowerCamelCase             =		"This is a test string"
           lowerCamelCase             =		"speaker_embeddings_path.json"
           lowerCamelCase             =		"speaker_embeddings"







     def     _a   (self					,      **__a     ):






           '''simple docstring'''



           return AutoTokenizer.from_pretrained(self.checkpoint					,      **__a     )







     def     _a   (self     ):






           '''simple docstring'''



           shutil.rmtree(self.tmpdirname     )







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		self.get_tokenizer()

           lowerCamelCase             =		BarkProcessor(tokenizer=__a     )

           processor.save_pretrained(self.tmpdirname     )
           lowerCamelCase             =		BarkProcessor.from_pretrained(self.tmpdirname     )

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







     @slow
     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		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					,      )

           lowerCamelCase             =		self.get_tokenizer(bos_token="(BOS)"					,      eos_token="(EOS)"     )

           lowerCamelCase             =		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     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		BarkProcessor.from_pretrained(
               pretrained_processor_name_or_path=self.checkpoint					,      speaker_embeddings_dict_path=self.speaker_embeddings_dict_path					,      )

           lowerCamelCase             =		35
           lowerCamelCase             =		2
           lowerCamelCase             =		8

           lowerCamelCase             =		{
               "semantic_prompt": np.ones(__a     ),
               "coarse_prompt": np.ones((nb_codebooks_coarse, seq_len)     ),
               "fine_prompt": np.ones((nb_codebooks_total, seq_len)     ),
           }

           # test providing already loaded voice_preset
           lowerCamelCase             =		processor(text=self.input_string					,      voice_preset=__a     )

           lowerCamelCase             =		inputs["history_prompt"]
           for key in voice_preset:
                 self.assertListEqual(voice_preset[key].tolist()					,      processed_voice_preset.get(__a					,      np.array([]     )     ).tolist()     )

           # test loading voice preset from npz file
           lowerCamelCase             =		os.path.join(self.tmpdirname					,      "file.npz"     )
           np.savez(__a					,      **__a     )
           lowerCamelCase             =		processor(text=self.input_string					,      voice_preset=__a     )
           lowerCamelCase             =		inputs["history_prompt"]

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

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







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		self.get_tokenizer()

           lowerCamelCase             =		BarkProcessor(tokenizer=__a     )

           lowerCamelCase             =		processor(text=self.input_string     )

           lowerCamelCase             =		tokenizer(
               self.input_string					,      padding="max_length"					,      max_length=2_56					,      add_special_tokens=__a					,      return_attention_mask=__a					,      return_token_type_ids=__a					,      )

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




import socket

def      __lowercase(						):


      """simple docstring"""



      lowerCamelCase             =		socket.socket(socket.AF_INET , socket.SOCK_STREAM			)
      lowerCamelCase             =		socket.gethostname()
      lowerCamelCase             =		12312

      sock.connect((host, port)			)
      sock.send(B"Hello server!"			)

      with open("Received_file" , "wb"			) as out_file:
            print("File opened"			)
            print("Receiving data..."			)
            while True:
                  lowerCamelCase             =		sock.recv(1024			)
                  if not data:
                        break
                  out_file.write(UpperCAmelCase__			)

      print("Successfully received the file"			)
      sock.close()
      print("Connection closed"			)


if __name__ == "__main__":
     main()