






import argparse
import os
import re


SCREAMING_SNAKE_CASE 							=						'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
SCREAMING_SNAKE_CASE 							=						re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
SCREAMING_SNAKE_CASE 							=						re.compile(R'\s*\(\s*"(\S[^"]+)"')

def      _lowerCamelCase	(						__A    :							Optional[int]		,		__A    :							bool = False )      ->					int:
    with open(__A		,		'''r'''		,		encoding='''utf-8''' ) as f:
        _UpperCAmelCase				:      Union[str, Any]			  =				f.read()

    _UpperCAmelCase				:      Any			  =				content.split('''\n''' )
    _UpperCAmelCase				:      Any			  =				[]
    _UpperCAmelCase				:      Tuple			  =				0
    while line_idx < len(__A ):
        if _re_intro_mapping.search(lines[line_idx] ) is not None:
            _UpperCAmelCase				:      Union[str, Any]			  =				len(re.search(r'''^(\s*)\S'''		,		lines[line_idx] ).groups()[0] ) + 8
            # Start of a new mapping!
            while not lines[line_idx].startswith(''' ''' * indent + '''(''' ):
                new_lines.append(lines[line_idx] )
                line_idx += 1

            _UpperCAmelCase				:      str			  =				[]
            while lines[line_idx].strip() != "]":
                # Blocks either fit in one line or not
                if lines[line_idx].strip() == "(":
                    _UpperCAmelCase				:      List[str]			  =				line_idx
                    while not lines[line_idx].startswith(''' ''' * indent + ''')''' ):
                        line_idx += 1
                    blocks.append('''\n'''.join(lines[start_idx : line_idx + 1] ) )
                else:
                    blocks.append(lines[line_idx] )
                line_idx += 1

            # Sort blocks by their identifiers
            _UpperCAmelCase				:      Tuple			  =				sorted(__A		,		key=lambda __A : _re_identifier.search(__A ).groups()[0] )
            new_lines += blocks
        else:
            new_lines.append(lines[line_idx] )
            line_idx += 1

    if overwrite:
        with open(__A		,		'''w'''		,		encoding='''utf-8''' ) as f:
            f.write('''\n'''.join(__A ) )
    elif "\n".join(__A ) != content:
        return True

def      _lowerCamelCase	(						__A    :							bool = False )      ->					List[str]:
    _UpperCAmelCase				:      List[str]			  =				[os.path.join(__A		,		__A ) for f in os.listdir(__A ) if f.endswith('''.py''' )]
    _UpperCAmelCase				:      List[Any]			  =				[sort_auto_mapping(__A		,		overwrite=__A ) for fname in fnames]

    if not overwrite and any(__A ):
        _UpperCAmelCase				:      Optional[int]			  =				[f for f, d in zip(__A		,		__A ) if d]
        raise ValueError(
            f'''The following files have auto mappings that need sorting: {', '.join(__A )}. Run `make style` to fix'''
            ''' this.''' )


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE 							=						argparse.ArgumentParser()
  parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
  SCREAMING_SNAKE_CASE 							=						parser.parse_args()

  sort_all_auto_mappings(not args.check_only)












import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
  # Create universe of discourse in Python using linspace ()
  SCREAMING_SNAKE_CASE 							=						np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)

  # Create two fuzzy sets by defining any membership function
  # (trapmf(), gbellmf(), gaussmf(), etc).
  SCREAMING_SNAKE_CASE 							=						[0, 25, 50]
  SCREAMING_SNAKE_CASE 							=						[25, 50, 75]
  SCREAMING_SNAKE_CASE 							=						fuzz.membership.trimf(X, abca)
  SCREAMING_SNAKE_CASE 							=						fuzz.membership.trimf(X, abca)

  # Compute the different operations using inbuilt functions.
  SCREAMING_SNAKE_CASE 							=						np.ones(75)
  SCREAMING_SNAKE_CASE 							=						np.zeros((75,))
  # 1. Union = max(µA(x), µB(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_or(X, young, X, middle_aged)[1]
  # 2. Intersection = min(µA(x), µB(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, young, X, middle_aged)[1]
  # 3. Complement (A) = (1- min(µA(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_not(young)
  # 4. Difference (A/B) = min(µA(x),(1- µB(x)))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
  # 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
  SCREAMING_SNAKE_CASE 							=						young + middle_aged - (young * middle_aged)
  # 6. Algebraic Product = (µA(x) * µB(x))
  SCREAMING_SNAKE_CASE 							=						young * middle_aged
  # 7. Bounded Sum = min[1,(µA(x), µB(x))]
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
  # 8. Bounded difference = min[0,(µA(x), µB(x))]
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]

  # max-min composition
  # max-product composition

  # Plot each set A, set B and each operation result using plot() and subplot().
  from matplotlib import pyplot as plt

  plt.figure()

  plt.subplot(4, 3, 1)
  plt.plot(X, young)
  plt.title('Young')
  plt.grid(True)

  plt.subplot(4, 3, 2)
  plt.plot(X, middle_aged)
  plt.title('Middle aged')
  plt.grid(True)

  plt.subplot(4, 3, 3)
  plt.plot(X, union)
  plt.title('union')
  plt.grid(True)

  plt.subplot(4, 3, 4)
  plt.plot(X, intersection)
  plt.title('intersection')
  plt.grid(True)

  plt.subplot(4, 3, 5)
  plt.plot(X, complement_a)
  plt.title('complement_a')
  plt.grid(True)

  plt.subplot(4, 3, 6)
  plt.plot(X, difference)
  plt.title('difference a/b')
  plt.grid(True)

  plt.subplot(4, 3, 7)
  plt.plot(X, alg_sum)
  plt.title('alg_sum')
  plt.grid(True)

  plt.subplot(4, 3, 8)
  plt.plot(X, alg_product)
  plt.title('alg_product')
  plt.grid(True)

  plt.subplot(4, 3, 9)
  plt.plot(X, bdd_sum)
  plt.title('bdd_sum')
  plt.grid(True)

  plt.subplot(4, 3, 10)
  plt.plot(X, bdd_difference)
  plt.title('bdd_difference')
  plt.grid(True)

  plt.subplots_adjust(hspace=0.5)
  plt.show()




