




import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
		# Create universe of discourse in Python using linspace ()
		UpperCAmelCase_						=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).
		UpperCAmelCase_						=[0, 25, 50]
		UpperCAmelCase_						=[25, 50, 75]
		UpperCAmelCase_						=fuzz.membership.trimf(X, abca)
		UpperCAmelCase_						=fuzz.membership.trimf(X, abca)

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









from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml


class 							__UpperCamelCase			( yaml.SafeLoader  ):





				'''simple docstring'''



				def       __snake_case		( self       , UpperCAmelCase_						):
											lowerCAmelCase   =		[self.constructed_objects[key_node] for key_node, _ in node.value]
											lowerCAmelCase   =		[tuple(UpperCAmelCase_						) if isinstance(UpperCAmelCase_       , UpperCAmelCase_						) else key for key in keys]
											lowerCAmelCase   =		Counter(UpperCAmelCase_						)
											lowerCAmelCase   =		[key for key in counter if counter[key] > 1]
											if duplicate_keys:
																		raise TypeError(F"""Got duplicate yaml keys: {duplicate_keys}"""						)






				def       __snake_case		( self       , UpperCAmelCase_       , UpperCAmelCase_=False						):
											lowerCAmelCase   =		super().construct_mapping(UpperCAmelCase_       , deep=UpperCAmelCase_						)
											self._check_no_duplicates_on_constructed_node(UpperCAmelCase_						)
											return mapping




def       UpperCAmelCase       (     _snake_case							):
							lowerCAmelCase   =		list(readme_content.splitlines()							)
							if full_content and full_content[0] == "---" and "---" in full_content[1:]:
														lowerCAmelCase   =		full_content[1:].index('''---'''							) + 1
														lowerCAmelCase   =		'''\n'''.join(full_content[1:sep_idx]							)
														return yamlblock, "\n".join(full_content[sep_idx + 1 :]							)

							return None, "\n".join(_snake_case							)


class 							__UpperCamelCase			( __UpperCAmelCase  ):





				'''simple docstring'''



				__a							: Any										={"""train_eval_index"""}  # train-eval-index in the YAML metadata



				@classmethod
				def       __snake_case		( cls       , UpperCAmelCase_						):
											with open(UpperCAmelCase_       , encoding='''utf-8'''						) as readme_file:
																		lowerCAmelCase   ,     lowerCAmelCase   =		_split_yaml_from_readme(readme_file.read()						)
											if yaml_string is not None:
																		return cls.from_yaml_string(UpperCAmelCase_						)
											else:
																		return cls()



				def       __snake_case		( self       , UpperCAmelCase_						):
											if path.exists():
																		with open(UpperCAmelCase_       , encoding='''utf-8'''						) as readme_file:
																									lowerCAmelCase   =		readme_file.read()
											else:
																		lowerCAmelCase   =		None
											lowerCAmelCase   =		self._to_readme(UpperCAmelCase_						)
											with open(UpperCAmelCase_       , '''w'''       , encoding='''utf-8'''						) as readme_file:
																		readme_file.write(UpperCAmelCase_						)



				def       __snake_case		( self       , UpperCAmelCase_ = None						):
											if readme_content is not None:
																		lowerCAmelCase   ,     lowerCAmelCase   =		_split_yaml_from_readme(UpperCAmelCase_						)
																		lowerCAmelCase   =		'''---\n''' + self.to_yaml_string() + '''---\n''' + content
											else:
																		lowerCAmelCase   =		'''---\n''' + self.to_yaml_string() + '''---\n'''
											return full_content



				@classmethod
				def       __snake_case		( cls       , UpperCAmelCase_						):
											lowerCAmelCase   =		yaml.load(UpperCAmelCase_       , Loader=_NoDuplicateSafeLoader						) or {}

											# Convert the YAML keys to DatasetMetadata fields
											lowerCAmelCase   =		{
											    (key.replace('''-'''       , '''_'''						) if key.replace('''-'''       , '''_'''						) in cls._FIELDS_WITH_DASHES else key): value
											    for key, value in metadata_dict.items()
											}
											return cls(**UpperCAmelCase_						)






				def       __snake_case		( self						):
											return yaml.safe_dump(
											    {
											        (key.replace('''_'''       , '''-'''						) if key in self._FIELDS_WITH_DASHES else key): value
											        for key, value in self.items()
											    }       , sort_keys=UpperCAmelCase_       , allow_unicode=UpperCAmelCase_       , encoding='''utf-8'''       , ).decode('''utf-8'''						)




UpperCAmelCase_						={
    """image-classification""": [],
    """translation""": [],
    """image-segmentation""": [],
    """fill-mask""": [],
    """automatic-speech-recognition""": [],
    """token-classification""": [],
    """sentence-similarity""": [],
    """audio-classification""": [],
    """question-answering""": [],
    """summarization""": [],
    """zero-shot-classification""": [],
    """table-to-text""": [],
    """feature-extraction""": [],
    """other""": [],
    """multiple-choice""": [],
    """text-classification""": [],
    """text-to-image""": [],
    """text2text-generation""": [],
    """zero-shot-image-classification""": [],
    """tabular-classification""": [],
    """tabular-regression""": [],
    """image-to-image""": [],
    """tabular-to-text""": [],
    """unconditional-image-generation""": [],
    """text-retrieval""": [],
    """text-to-speech""": [],
    """object-detection""": [],
    """audio-to-audio""": [],
    """text-generation""": [],
    """conversational""": [],
    """table-question-answering""": [],
    """visual-question-answering""": [],
    """image-to-text""": [],
    """reinforcement-learning""": [],
    """voice-activity-detection""": [],
    """time-series-forecasting""": [],
    """document-question-answering""": [],
}


if __name__ == "__main__":
		from argparse import ArgumentParser

		UpperCAmelCase_						=ArgumentParser(usage="""Validate the yaml metadata block of a README.md file.""")
		ap.add_argument("""readme_filepath""")
		UpperCAmelCase_						=ap.parse_args()

		UpperCAmelCase_						=Path(args.readme_filepath)
		UpperCAmelCase_						=DatasetMetadata.from_readme(readme_filepath)
		print(dataset_metadata)
		dataset_metadata.to_readme(readme_filepath)



