'''simple docstring'''






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    a (       unittest.TestCase				):



  """simple docstring"""







  def    lowercase_  (							self					):

    '''simple docstring'''







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







  def    lowercase_  (							self   ,    **snake_case_					):

    '''simple docstring'''







    return AutoTokenizer.from_pretrained(self.checkpoint   ,    **snake_case_					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    shutil.rmtree(self.tmpdirname					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Any		= self.get_tokenizer()

    __UpperCAmelCase:					List[str]		= BarkProcessor(tokenizer=snake_case_					)

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

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







  @slow
  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					List[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   ,    )

    __UpperCAmelCase:					str		= self.get_tokenizer(bos_token="""(BOS)"""   ,    eos_token="""(EOS)"""					)

    __UpperCAmelCase:					Dict		= 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    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					str		= BarkProcessor.from_pretrained(
        pretrained_processor_name_or_path=self.checkpoint   ,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path   ,    )

    __UpperCAmelCase:					Any		= 35
    __UpperCAmelCase:					Dict		= 2
    __UpperCAmelCase:					int		= 8

    __UpperCAmelCase:					Tuple		= {
        """semantic_prompt""": np.ones(snake_case_					),
        """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:					Any		= processor(text=self.input_string   ,    voice_preset=snake_case_					)

    __UpperCAmelCase:					Union[str, Any]		= inputs["""history_prompt"""]
    for key in voice_preset:
      self.assertListEqual(voice_preset[key].tolist()   ,    processed_voice_preset.get(snake_case_   ,    np.array([]					)					).tolist()					)

    # test loading voice preset from npz file
    __UpperCAmelCase:					List[Any]		= os.path.join(self.tmpdirname   ,    """file.npz"""					)
    np.savez(snake_case_   ,    **snake_case_					)
    __UpperCAmelCase:					Union[str, Any]		= processor(text=self.input_string   ,    voice_preset=snake_case_					)
    __UpperCAmelCase:					int		= inputs["""history_prompt"""]

    for key in voice_preset:
      self.assertListEqual(voice_preset[key].tolist()   ,    processed_voice_preset.get(snake_case_   ,    np.array([]					)					).tolist()					)

    # test loading voice preset from the hub
    __UpperCAmelCase:					List[Any]		= processor(text=self.input_string   ,    voice_preset=self.voice_preset					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Tuple		= self.get_tokenizer()

    __UpperCAmelCase:					Tuple		= BarkProcessor(tokenizer=snake_case_					)

    __UpperCAmelCase:					Tuple		= processor(text=self.input_string					)

    __UpperCAmelCase:					Optional[int]		= tokenizer(
        self.input_string   ,    padding="""max_length"""   ,    max_length=256   ,    add_special_tokens=snake_case_   ,    return_attention_mask=snake_case_   ,    return_token_type_ids=snake_case_   ,    )

    for key in encoded_tok.keys():
      self.assertListEqual(encoded_tok[key]   ,    encoded_processor[key].squeeze().tolist()					)
'''simple docstring'''






def  UpperCamelCase__					(					_lowercase    :				List[str]     )							->	Union[str, Any]:
  __UpperCAmelCase:					int		= []
  __UpperCAmelCase:					List[Any]		= []
  __UpperCAmelCase:					List[Any]		= {
      """^""": 3,
      """*""": 2,
      """/""": 2,
      """%""": 2,
      """+""": 1,
      """-""": 1,
  }  # Priority of each operator
  __UpperCAmelCase:					int		= len(_lowercase     ) if (len(_lowercase     ) > 7) else 7

  # Print table header for output
  print(
      """Symbol""".center(8     )   ,    """Stack""".center(_lowercase     )   ,    """Postfix""".center(_lowercase     )   ,    sep=""" | """   ,    )
  print("""-""" * (print_width * 3 + 7)     )

  for x in infix:
    if x.isalpha() or x.isdigit():
      post_fix.append(_lowercase     )  # if x is Alphabet / Digit, add it to Postfix
    elif x == "(":
      stack.append(_lowercase     )  # if x is "(" push to Stack
    elif x == ")":  # if x is ")" pop stack until "(" is encountered
      while stack[-1] != "(":
        post_fix.append(stack.pop()     )  # Pop stack & add the content to Postfix
      stack.pop()
    else:
      if len(_lowercase     ) == 0:
        stack.append(_lowercase     )  # If stack is empty, push x to stack
      else:  # while priority of x is not > priority of element in the stack
        while len(_lowercase     ) > 0 and priority[x] <= priority[stack[-1]]:
          post_fix.append(stack.pop()     )  # pop stack & add to Postfix
        stack.append(_lowercase     )  # push x to stack

    print(
        x.center(8     )   ,    ("""""".join(_lowercase     )).ljust(_lowercase     )   ,    ("""""".join(_lowercase     )).ljust(_lowercase     )   ,    sep=""" | """   ,    )  # Output in tabular format

  while len(_lowercase     ) > 0:  # while stack is not empty
    post_fix.append(stack.pop()     )  # pop stack & add to Postfix
    print(
        """ """.center(8     )   ,    ("""""".join(_lowercase     )).ljust(_lowercase     )   ,    ("""""".join(_lowercase     )).ljust(_lowercase     )   ,    sep=""" | """   ,    )  # Output in tabular format

  return "".join(_lowercase     )  # return Postfix as str






def  UpperCamelCase__					(					_lowercase    :				str     )							->	Tuple:
  __UpperCAmelCase:					Union[str, Any]		= list(infix[::-1]     )  # reverse the infix equation

  for i in range(len(_lowercase     )     ):
    if infix[i] == "(":
      __UpperCAmelCase:					Tuple		= """)"""  # change "(" to ")"
    elif infix[i] == ")":
      __UpperCAmelCase:					Union[str, Any]		= """("""  # change ")" to "("

  return (infix_2_postfix("""""".join(_lowercase     )     ))[
      ::-1
  ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
    SCREAMING_SNAKE_CASE_	   =			input('\nEnter an Infix Equation = ')  # Input an Infix equation
    SCREAMING_SNAKE_CASE_	   =			''.join(Infix.split())  # Remove spaces from the input
    print('\n\t', Infix, '(Infix) -> ', infix_2_prefix(Infix), '(Prefix)')