






__snake_case      :      Optional[Any]             =       2_56
# Modulus to hash a string
__snake_case      :      Tuple             =       1_00_00_03







def 		_UpperCamelCase				(      lowerCAmelCase    :   str      ,    lowerCAmelCase    :   str						)					->				bool:

						"""simple docstring"""



						lowerCAmelCase__        =  len(lowerCAmelCase						)
						lowerCAmelCase__        =  len(lowerCAmelCase						)
						if p_len > t_len:
												return False

						lowerCAmelCase__        =  0
						lowerCAmelCase__        =  0
						lowerCAmelCase__        =  1

						# Calculating the hash of pattern and substring of text
						for i in range(lowerCAmelCase						):
												lowerCAmelCase__        =  (ord(pattern[i]						) + p_hash * alphabet_size) % modulus
												lowerCAmelCase__        =  (ord(text[i]						) + text_hash * alphabet_size) % modulus
												if i == p_len - 1:
																		continue
												lowerCAmelCase__        =  (modulus_power * alphabet_size) % modulus

						for i in range(0      ,    t_len - p_len + 1						):
												if text_hash == p_hash and text[i : i + p_len] == pattern:
																		return True
												if i == t_len - p_len:
																		continue
												# Calculate the https://en.wikipedia.org/wiki/Rolling_hash
												lowerCAmelCase__        =  (
												    (text_hash - ord(text[i]						) * modulus_power) * alphabet_size
												    + ord(text[i + p_len]						)
												) % modulus
						return False







def 		_UpperCamelCase				(      )					->				None:

						"""simple docstring"""



						lowerCAmelCase__        =  '''abc1abc12'''
						lowerCAmelCase__        =  '''alskfjaldsabc1abc1abc12k23adsfabcabc'''
						lowerCAmelCase__        =  '''alskfjaldsk23adsfabcabc'''
						assert rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						) and not rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)

						# Test 2)
						lowerCAmelCase__        =  '''ABABX'''
						lowerCAmelCase__        =  '''ABABZABABYABABX'''
						assert rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)

						# Test 3)
						lowerCAmelCase__        =  '''AAAB'''
						lowerCAmelCase__        =  '''ABAAAAAB'''
						assert rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)

						# Test 4)
						lowerCAmelCase__        =  '''abcdabcy'''
						lowerCAmelCase__        =  '''abcxabcdabxabcdabcdabcy'''
						assert rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)

						# Test 5)
						lowerCAmelCase__        =  '''Lü'''
						lowerCAmelCase__        =  '''Lüsai'''
						assert rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)
						lowerCAmelCase__        =  '''Lue'''
						assert not rabin_karp(lowerCAmelCase      ,    lowerCAmelCase						)
						print('Success.'						)


if __name__ == "__main__":
					test_rabin_karp()













# 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       __SCREAMING_SNAKE_CASE   (				__lowercase):
						_SCREAMING_SNAKE_CASE		:    List[Any]						=   '''microsoft/speecht5_tts'''
						_SCREAMING_SNAKE_CASE		:    Any						=   (
						    '''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.'''
						)
						_SCREAMING_SNAKE_CASE		:    int						=   '''text_reader'''
						_SCREAMING_SNAKE_CASE		:    List[str]						=   SpeechTaProcessor
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   SpeechTaForTextToSpeech
						_SCREAMING_SNAKE_CASE		:    List[Any]						=   SpeechTaHifiGan

						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   ['''text''']
						_SCREAMING_SNAKE_CASE		:    List[Any]						=   ['''audio''']






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												if self.post_processor is None:
																		lowerCAmelCase__        =  'microsoft/speecht5_hifigan'
												super().setup()






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






												"""simple docstring"""
												lowerCAmelCase__        =  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.'				)

																		lowerCAmelCase__        =  load_dataset('Matthijs/cmu-arctic-xvectors'       ,  split='validation'				)
																		lowerCAmelCase__        =  torch.tensor(embeddings_dataset[73_05]['xvector']				).unsqueeze(0				)

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






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												with torch.no_grad():
																		return self.model.generate_speech(**_UpperCamelCase				)







						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												with torch.no_grad():
																		return self.post_processor(_UpperCamelCase				).cpu().detach()





