"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest

from transformers import is_speech_available, is_torch_available
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_torch
from transformers.utils import FEATURE_EXTRACTOR_NAME


if is_speech_available() and is_torch_available():
 from transformers import SpeechTaFeatureExtractor, SpeechTaProcessor

 from .test_feature_extraction_speechta import floats_list


lowercase__   			=      get_tests_dir('fixtures/test_sentencepiece_bpe_char.model')




@require_torch
class   __snake_case			(	unittest.TestCase							):



      def     lowerCamelCase_  (		self)      ->     Tuple:





        '''simple docstring'''





        a__:	int     				=      tempfile.mkdtemp()

        a__:	Optional[Any]     				=      SpeechTaTokenizer(lowercase)
        tokenizer.save_pretrained(self.tmpdirname)

        a__:	List[str]     				=      {
            """feature_size""": 1,
            """padding_value""": 0.0,
            """sampling_rate""": 1_60_00,
            """do_normalize""": False,
            """num_mel_bins""": 80,
            """hop_length""": 16,
            """win_length""": 64,
            """win_function""": """hann_window""",
            """fmin""": 80,
            """fmax""": 76_00,
            """mel_floor""": 1e-10,
            """reduction_factor""": 2,
            """return_attention_mask""": True,
        }

        a__:	List[str]     				=      os.path.join(self.tmpdirname       ,     lowercase)
        with open(self.feature_extraction_file       ,     'w'       ,     encoding='utf-8') as fp:
          fp.write(json.dumps(lowercase) + '\n')



      def     lowerCamelCase_  (		self       ,     **lowercase)      ->     List[str]:





        '''simple docstring'''





        return SpeechTaTokenizer.from_pretrained(self.tmpdirname       ,     **lowercase)



      def     lowerCamelCase_  (		self       ,     **lowercase)      ->     Any:





        '''simple docstring'''





        return SpeechTaFeatureExtractor.from_pretrained(self.tmpdirname       ,     **lowercase)



      def     lowerCamelCase_  (		self)      ->     Any:





        '''simple docstring'''





        shutil.rmtree(self.tmpdirname)



      def     lowerCamelCase_  (		self)      ->     Tuple:





        '''simple docstring'''





        a__:	str     				=      self.get_tokenizer()
        a__:	Optional[int]     				=      self.get_feature_extractor()

        a__:	List[Any]     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        processor.save_pretrained(self.tmpdirname)
        a__:	Any     				=      SpeechTaProcessor.from_pretrained(self.tmpdirname)

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

        self.assertEqual(processor.feature_extractor.to_json_string()       ,     feature_extractor.to_json_string())
        self.assertIsInstance(processor.feature_extractor       ,     lowercase)



      def     lowerCamelCase_  (		self)      ->     List[Any]:





        '''simple docstring'''





        a__:	str     				=      SpeechTaProcessor(tokenizer=self.get_tokenizer()       ,     feature_extractor=self.get_feature_extractor())
        processor.save_pretrained(self.tmpdirname)

        a__:	int     				=      self.get_tokenizer(bos_token='(BOS)'       ,     eos_token='(EOS)')
        a__:	List[str]     				=      self.get_feature_extractor(do_normalize=lowercase       ,     padding_value=1.0)

        a__:	str     				=      SpeechTaProcessor.from_pretrained(
            self.tmpdirname       ,     bos_token='(BOS)'       ,     eos_token='(EOS)'       ,     do_normalize=lowercase       ,     padding_value=1.0)

        self.assertEqual(processor.tokenizer.get_vocab()       ,     tokenizer_add_kwargs.get_vocab())
        self.assertIsInstance(processor.tokenizer       ,     lowercase)

        self.assertEqual(processor.feature_extractor.to_json_string()       ,     feature_extractor_add_kwargs.to_json_string())
        self.assertIsInstance(processor.feature_extractor       ,     lowercase)



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





        '''simple docstring'''





        a__:	List[str]     				=      self.get_feature_extractor()
        a__:	List[str]     				=      self.get_tokenizer()

        a__:	List[str]     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        a__:	Optional[int]     				=      floats_list((3, 10_00))

        a__:	str     				=      feature_extractor(audio=lowercase       ,     return_tensors='np')
        a__:	Any     				=      processor(audio=lowercase       ,     return_tensors='np')

        for key in input_feat_extract.keys():
          self.assertAlmostEqual(input_feat_extract[key].sum()       ,     input_processor[key].sum()       ,     delta=1e-2)



      def     lowerCamelCase_  (		self)      ->     List[str]:





        '''simple docstring'''





        a__:	Optional[int]     				=      self.get_feature_extractor()
        a__:	Any     				=      self.get_tokenizer()

        a__:	int     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        a__:	Dict     				=      floats_list((3, 10_00))

        a__:	Optional[Any]     				=      feature_extractor(audio_target=lowercase       ,     return_tensors='np')
        a__:	Union[str, Any]     				=      processor(audio_target=lowercase       ,     return_tensors='np')

        for key in input_feat_extract.keys():
          self.assertAlmostEqual(input_feat_extract[key].sum()       ,     input_processor[key].sum()       ,     delta=1e-2)



      def     lowerCamelCase_  (		self)      ->     List[Any]:





        '''simple docstring'''





        a__:	Tuple     				=      self.get_feature_extractor()
        a__:	List[Any]     				=      self.get_tokenizer()

        a__:	Union[str, Any]     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        a__:	Dict     				=      """This is a test string"""

        a__:	Optional[Any]     				=      processor(text=lowercase)
        a__:	Any     				=      tokenizer(lowercase)

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



      def     lowerCamelCase_  (		self)      ->     List[Any]:





        '''simple docstring'''





        a__:	int     				=      self.get_feature_extractor()
        a__:	Optional[int]     				=      self.get_tokenizer()

        a__:	int     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        a__:	Any     				=      """This is a test string"""

        a__:	Optional[int]     				=      processor(text_target=lowercase)
        a__:	Union[str, Any]     				=      tokenizer(lowercase)

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



      def     lowerCamelCase_  (		self)      ->     int:





        '''simple docstring'''





        a__:	List[Any]     				=      self.get_feature_extractor()
        a__:	str     				=      self.get_tokenizer()

        a__:	Optional[int]     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        a__:	int     				=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        a__:	Optional[Any]     				=      processor.batch_decode(lowercase)
        a__:	Any     				=      tokenizer.batch_decode(lowercase)

        self.assertListEqual(lowercase       ,     lowercase)



      def     lowerCamelCase_  (		self)      ->     Dict:





        '''simple docstring'''





        a__:	List[Any]     				=      self.get_feature_extractor()
        a__:	str     				=      self.get_tokenizer()

        a__:	Dict     				=      SpeechTaProcessor(tokenizer=lowercase       ,     feature_extractor=lowercase)

        self.assertListEqual(
            processor.model_input_names       ,     feature_extractor.model_input_names       ,     msg='`processor` and `feature_extractor` model input names do not match'       ,     )







'''simple docstring'''




from __future__ import annotations



def  __lowerCamelCase    (   _lowercase						) ->     int | None:
							for r in range(1      ,							_lowercase						):
														UpperCAmelCase	:						Dict					=						[]
														for x in range(n - 1						):
																					UpperCAmelCase	:						List[str]					=						pow(_lowercase      ,							_lowercase      ,							_lowercase						)
																					if val in li:
																												break
																					li.append(_lowercase						)
														else:
																					return r
							return None


if __name__ == "__main__":
							a  :     Dict       =       int(input("""Enter a prime number q: """))
							a  :     Union[str, Any]       =       find_primitive(q)
							if a is None:
														print(F'''Cannot find the primitive for the value: {a!r}''')
							else:
														a  :     str       =       int(input("""Enter private key of A: """))
														a  :     str       =       pow(a, a_private, q)
														a  :     List[Any]       =       int(input("""Enter private key of B: """))
														a  :     str       =       pow(a, b_private, q)

														a  :     Union[str, Any]       =       pow(b_public, a_private, q)
														a  :     List[Any]       =       pow(a_public, b_private, q)

														print("""The key value generated by A is: """, a_secret)
														print("""The key value generated by B is: """, b_secret)

