
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   ):





   '''simple docstring'''


   def  __magic_name__				(					self     :							int     ):

      """simple docstring"""
      _A:  List[str]					=       '''ylacombe/bark-small'''
      _A:  Optional[int]					=       tempfile.mkdtemp()
      _A:  List[Any]					=       '''en_speaker_1'''
      _A:  Tuple					=       '''This is a test string'''
      _A:  Any					=       '''speaker_embeddings_path.json'''
      _A:  int					=       '''speaker_embeddings'''


   def  __magic_name__				(					self     :							Optional[int]			,			**lowerCAmelCase_     :							str     ):

      """simple docstring"""
      return AutoTokenizer.from_pretrained(self.checkpoint			,			**lowerCAmelCase_     )


   def  __magic_name__				(					self     :							str     ):

      """simple docstring"""
      shutil.rmtree(self.tmpdirname     )


   def  __magic_name__				(					self     :							Optional[int]     ):

      """simple docstring"""
      _A:  Union[str, Any]					=       self.get_tokenizer()

      _A:  Tuple					=       BarkProcessor(tokenizer=lowerCAmelCase_     )

      processor.save_pretrained(self.tmpdirname     )
      _A:  Union[str, Any]					=       BarkProcessor.from_pretrained(self.tmpdirname     )

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


   @slow
   def  __magic_name__				(					self     :							List[Any]     ):

      """simple docstring"""
      _A:  Any					=       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			,			)

      _A:  Optional[Any]					=       self.get_tokenizer(bos_token='''(BOS)'''			,			eos_token='''(EOS)'''     )

      _A:  Optional[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  __magic_name__				(					self     :							Any     ):

      """simple docstring"""
      _A:  Union[str, Any]					=       BarkProcessor.from_pretrained(
          pretrained_processor_name_or_path=self.checkpoint			,			speaker_embeddings_dict_path=self.speaker_embeddings_dict_path			,			)

      _A:  Union[str, Any]					=       3_5
      _A:  int					=       2
      _A:  Tuple					=       8

      _A:  Union[str, Any]					=       {
          '''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
      _A:  Optional[int]					=       processor(text=self.input_string			,			voice_preset=lowerCAmelCase_     )

      _A:  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 npz file
      _A:  int					=       os.path.join(self.tmpdirname			,			'''file.npz'''     )
      np.savez(lowerCAmelCase_			,			**lowerCAmelCase_     )
      _A:  str					=       processor(text=self.input_string			,			voice_preset=lowerCAmelCase_     )
      _A:  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 the hub
      _A:  Optional[Any]					=       processor(text=self.input_string			,			voice_preset=self.voice_preset     )


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

      """simple docstring"""
      _A:  str					=       self.get_tokenizer()

      _A:  Tuple					=       BarkProcessor(tokenizer=lowerCAmelCase_     )

      _A:  str					=       processor(text=self.input_string     )

      _A:  List[str]					=       tokenizer(
          self.input_string			,			padding='''max_length'''			,			max_length=2_5_6			,			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()     )





import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

UpperCAmelCase__		:     Any     			=      3






def   lowerCamelCase__							(					a      )      ->   int:
   print('''Generating primitive root of p'''      )
   while True:
      _A:  Union[str, Any]					=       random.randrange(3		,		a      )
      if pow(a		,		2		,		a      ) == 1:
         continue
      if pow(a		,		a		,		a      ) == 1:
         continue
      return g






def   lowerCamelCase__							(					a      )      ->   tuple[tuple[int, int, int, int], tuple[int, int]]:
   print('''Generating prime p...'''      )
   _A:  Dict					=       rabin_miller.generate_large_prime(a      )  # select large prime number.
   _A:  Any					=       primitive_root(a      )  # one primitive root on modulo p.
   _A:  Optional[Any]					=       random.randrange(3		,		a      )  # private_key -> have to be greater than 2 for safety.
   _A:  Dict					=       cryptomath.find_mod_inverse(pow(a		,		a		,		a      )		,		a      )

   _A:  Union[str, Any]					=       (key_size, e_a, e_a, p)
   _A:  Union[str, Any]					=       (key_size, d)

   return public_key, private_key






def   lowerCamelCase__							(					a		,		a      )      ->   None:
   if os.path.exists(f"""{name}_pubkey.txt"""      ) or os.path.exists(f"""{name}_privkey.txt"""      ):
      print('''\nWARNING:'''      )
      print(
          f"""\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"""
          '''Use a different name or delete these files and re-run this program.'''      )
      sys.exit()

   _A			,  _A:  Any					=       generate_key(a      )
   print(f"""\nWriting public key to file {name}_pubkey.txt..."""      )
   with open(f"""{name}_pubkey.txt"""		,		'''w'''      ) as fo:
      fo.write(f"""{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"""      )

   print(f"""Writing private key to file {name}_privkey.txt..."""      )
   with open(f"""{name}_privkey.txt"""		,		'''w'''      ) as fo:
      fo.write(f"""{private_key[0]},{private_key[1]}"""      )






def   lowerCamelCase__							(					)      ->   None:
   print('''Making key files...'''      )
   make_key_files('''elgamal'''		,		20_48      )
   print('''Key files generation successful'''      )


if __name__ == "__main__":
   main()



