


import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class     lowercase__  (					__SCREAMING_SNAKE_CASE					,							unittest.TestCase		):
  A__=  OpenAIGPTTokenizer
  A__=  OpenAIGPTTokenizerFast
  A__=  True
  A__=  False






  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         UpperCAmelCase__										=     [
             "l",
             "o",
             "w",
             "e",
             "r",
             "s",
             "t",
             "i",
             "d",
             "n",
             "w</w>",
             "r</w>",
             "t</w>",
             "lo",
             "low",
             "er</w>",
             "low</w>",
             "lowest</w>",
             "newer</w>",
             "wider</w>",
             "<unk>",
         ]
         UpperCAmelCase__										=     dict(zip(_lowercase		,						range(len(_lowercase ) ) ) )
         UpperCAmelCase__										=     ["#version: 0.2", "l o", "lo w", "e r</w>", ""]

         UpperCAmelCase__										=     os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["vocab_file"] )
         UpperCAmelCase__										=     os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["merges_file"] )
         with open(self.vocab_file		,						"w" ) as fp:
                fp.write(json.dumps(_lowercase ) )
         with open(self.merges_file		,						"w" ) as fp:
                fp.write("\n".join(_lowercase ) )






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




         """simple docstring"""







         return "lower newer", "lower newer"






  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     OpenAIGPTTokenizer(self.vocab_file		,						self.merges_file )

         UpperCAmelCase__										=     "lower"
         UpperCAmelCase__										=     ["low", "er</w>"]
         UpperCAmelCase__										=     tokenizer.tokenize(_lowercase )
         self.assertListEqual(_lowercase		,						_lowercase )

         UpperCAmelCase__										=     tokens + ["<unk>"]
         UpperCAmelCase__										=     [14, 15, 20]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase )		,						_lowercase )






  def 			_UpperCAmelCase  (					self      :					Optional[int]		,						_lowercase      :					Tuple=15 ):




         """simple docstring"""







         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
                       UpperCAmelCase__										=     self.rust_tokenizer_class.from_pretrained(_lowercase		,						**_lowercase )

                       # Simple input
                       UpperCAmelCase__										=     "This is a simple input"
                       UpperCAmelCase__										=     ["This is a simple input 1", "This is a simple input 2"]
                       UpperCAmelCase__										=     ("This is a simple input", "This is a pair")
                       UpperCAmelCase__										=     [
                           ("This is a simple input 1", "This is a simple input 2"),
                           ("This is a simple pair 1", "This is a simple pair 2"),
                       ]

                       # Simple input tests
                       self.assertRaises(_lowercase		,						tokenizer_r.encode		,						_lowercase		,						max_length=_lowercase		,						padding="max_length" )

                       # Simple input
                       self.assertRaises(_lowercase		,						tokenizer_r.encode_plus		,						_lowercase		,						max_length=_lowercase		,						padding="max_length" )

                       # Simple input
                       self.assertRaises(
                           _lowercase		,						tokenizer_r.batch_encode_plus		,						_lowercase		,						max_length=_lowercase		,						padding="max_length"		,						)

                       # Pair input
                       self.assertRaises(_lowercase		,						tokenizer_r.encode		,						_lowercase		,						max_length=_lowercase		,						padding="max_length" )

                       # Pair input
                       self.assertRaises(_lowercase		,						tokenizer_r.encode_plus		,						_lowercase		,						max_length=_lowercase		,						padding="max_length" )

                       # Pair input
                       self.assertRaises(
                           _lowercase		,						tokenizer_r.batch_encode_plus		,						_lowercase		,						max_length=_lowercase		,						padding="max_length"		,						)






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         pass




@require_ftfy
@require_spacy
@require_tokenizers
class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
  pass









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() )





