





"""simple docstring"""





import pytest

from datasets import inspect_metric, list_metrics, load_metric


@pytest.fixture
def 					a__    (    _SCREAMING_SNAKE_CASE			):




		"""simple docstring"""


		monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"     ,		set()			)


@pytest.fixture
def 					a__    (    _SCREAMING_SNAKE_CASE			):




		"""simple docstring"""


		class 				_lowerCamelCase					:


								def __init__(self      ,							__a						)       ->      Optional[int]:
										UpperCamelCase      =		metric_id





		class 				_lowerCamelCase					:
								UpperCAmelCase_       =	[MetricMock(UpperCAmelCase_       ) for metric_id in ['accuracy', 'mse', 'precision', 'codeparrot/apps_metric']]


								def 			snake_case_      (self						)       ->      Union[str, Any]:
										return self._metrics



		monkeypatch.setattr("datasets.inspect.huggingface_hub"     ,		HfhMock()			)






@pytest.mark.parametrize(
    "func, args"     ,		[(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))]			)
def 					a__    (    _SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE			):




		"""simple docstring"""


		if "tmp_path" in args:
				UpperCamelCase      =		tuple(arg if arg != "tmp_path" else tmp_path for arg in args			)
		with pytest.warns(__A     ,		match="https://huggingface.co/docs/evaluate"			):
				func(*__A			)







import math
import random




def    lowerCAmelCase_ (     __A,  __A = False							)     ->				float:







      '''simple docstring'''


      if deriv:
            return value * (1 - value)
      return 1 / (1 + math.exp(-value							))


# Initial Value
UpperCamelCase__											=					0.0_2




def    lowerCAmelCase_ (     __A,  __A							)     ->				float:







      '''simple docstring'''


      UpperCAmelCase__								=  float(2 * (random.randint(1,  100							)) - 1							)

      for _ in range(__A							):
            # Forward propagation
            UpperCAmelCase__								=  sigmoid_function(INITIAL_VALUE * weight							)
            # How much did we miss?
            UpperCAmelCase__								=  (expected / 100) - layer_a
            # Error delta
            UpperCAmelCase__								=  layer_1_error * sigmoid_function(__A,  __A							)
            # Update weight
            weight += INITIAL_VALUE * layer_1_delta

      return layer_a * 100


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      UpperCamelCase__											=					int(input('Expected value: '))
      UpperCamelCase__											=					int(input('Number of propagations: '))
      print(forward_propagation(expected, number_propagations))



