

from argparse import ArgumentParser

from . import BaseTransformersCLICommand





def __UpperCAmelCase       (		__A			)						->					Optional[int]:



       '''simple docstring'''





       return DownloadCommand(args.model ,						args.cache_dir ,						args.force ,						args.trust_remote_code			)




class     lowercase__  (					_lowercase		):






  @staticmethod
  def 			_UpperCAmelCase  (					_lowercase      :					ArgumentParser ):




         """simple docstring"""







         UpperCAmelCase__										=     parser.add_parser("download" )
         download_parser.add_argument(
             "--cache-dir"		,						type=A_		,						default=A_		,						help="Path to location to store the models" )
         download_parser.add_argument(
             "--force"		,						action="store_true"		,						help="Force the model to be download even if already in cache-dir" )
         download_parser.add_argument(
             "--trust-remote-code"		,						action="store_true"		,						help="Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine"		,						)
         download_parser.add_argument("model"		,						type=A_		,						help="Name of the model to download" )
         download_parser.set_defaults(func=A_ )






  def __init__(					self      :					Dict		,						_lowercase      :					str		,						_lowercase      :					str		,						_lowercase      :					bool		,						_lowercase      :					bool ):




         """simple docstring"""







         UpperCAmelCase__										=     model
         UpperCAmelCase__										=     cache
         UpperCAmelCase__										=     force
         UpperCAmelCase__										=     trust_remote_code






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         from ..models.auto import AutoModel, AutoTokenizer

         AutoModel.from_pretrained(
             self._model		,						cache_dir=self._cache		,						force_download=self._force		,						trust_remote_code=self._trust_remote_code )
         AutoTokenizer.from_pretrained(
             self._model		,						cache_dir=self._cache		,						force_download=self._force		,						trust_remote_code=self._trust_remote_code )









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     lowercase__  (					unittest.TestCase		):






  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







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






  def 			_UpperCAmelCase  (					self      :					List[str]		,						**_lowercase      :					str ):




         """simple docstring"""







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






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         shutil.rmtree(self.tmpdirname )






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.get_tokenizer()

         UpperCAmelCase__										=     BarkProcessor(tokenizer=_lowercase )

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

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






  @slow
  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         UpperCAmelCase__										=     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		,						)

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

         UpperCAmelCase__										=     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      :					Optional[Any] ):




         """simple docstring"""







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

         UpperCAmelCase__										=     35
         UpperCAmelCase__										=     2
         UpperCAmelCase__										=     8

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

         # test providing already loaded voice_preset
         UpperCAmelCase__										=     processor(text=self.input_string		,						voice_preset=_lowercase )

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

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

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

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






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




         """simple docstring"""







         UpperCAmelCase__										=     self.get_tokenizer()

         UpperCAmelCase__										=     BarkProcessor(tokenizer=_lowercase )

         UpperCAmelCase__										=     processor(text=self.input_string )

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

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





