





"""simple docstring"""



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool


if is_datasets_available():
       from datasets import load_dataset






class 		__snake_case (		UpperCamelCase__					):





 """simple docstring"""


 _lowerCamelCase				=					'''microsoft/speecht5_tts'''
 _lowerCamelCase				=					(
     '''This is a tool that reads an English text out loud. It takes an input named `text` which should contain the '''
     '''text to read (in English) and returns a waveform object containing the sound.'''
 )
 _lowerCamelCase				=					'''text_reader'''
 _lowerCamelCase				=					SpeechTaProcessor
 _lowerCamelCase				=					SpeechTaForTextToSpeech
 _lowerCamelCase				=					SpeechTaHifiGan

 _lowerCamelCase				=					['''text''']
 _lowerCamelCase				=					['''audio''']

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     if self.post_processor is None:
         __A   :						Union[str, Any]									=					'''microsoft/speecht5_hifigan'''
     super().setup()

 def  UpperCamelCase__(   self ,						__lowerCamelCase ,						__lowerCamelCase=None  ):



     '''simple docstring'''




     __A   :						int									=					self.pre_processor(text=UpperCamelCase_ ,						return_tensors='''pt''' ,						truncation=UpperCamelCase_  )

     if speaker_embeddings is None:
         if not is_datasets_available():
             raise ImportError('''Datasets needs to be installed if not passing speaker embeddings.'''  )

         __A   :						Any									=					load_dataset('''Matthijs/cmu-arctic-xvectors''' ,						split='''validation'''  )
         __A   :						Dict									=					torch.tensor(embeddings_dataset[7305]['''xvector''']  ).unsqueeze(0  )

     return {"input_ids": inputs["input_ids"], "speaker_embeddings": speaker_embeddings}

 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     with torch.no_grad():
         return self.model.generate_speech(**UpperCamelCase_  )







 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     with torch.no_grad():
         return self.post_processor(UpperCamelCase_  ).cpu().detach()











"""simple docstring"""



import math
from collections.abc import Iterator
from itertools import takewhile







def 		__lowercase					(       snake_case_  :  int						)       ->bool:



    '''simple docstring'''







    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5    ,int(math.sqrt(snake_case_						) + 1						)    ,6						):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True







def 		__lowercase					(       )       ->Iterator[int]:



    '''simple docstring'''







    __A   :						int									=					2
    while True:
        if is_prime(snake_case_						):
            yield num
        num += 1







def 		__lowercase					(       snake_case_  :  int = 2000000						)       ->int:



    '''simple docstring'''







    return sum(takewhile(lambda snake_case_						: x < n    ,prime_generator()						)						)


if __name__ == "__main__":
       print(f'''{solution() = }''')




