




'''simple docstring'''

import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD


def 		__magic_name__    (	__UpperCAmelCase	)		->					Optional[int]:

					'''simple docstring'''

					def wrapper(*__UpperCAmelCase,      **__UpperCAmelCase	):
										snake_case_									=				timeit.default_timer()
										snake_case_									=				func(*__UpperCAmelCase,      **__UpperCAmelCase	)
										snake_case_									=				timeit.default_timer() - starttime
										return delta

					snake_case_									=				func.__name__

					return wrapper


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase=100,      __UpperCAmelCase=None	)		->					Optional[Any]:

					'''simple docstring'''

					snake_case_									=				[]
					snake_case_									=				seq_shapes or {}
					for i in range(__UpperCAmelCase	):
										snake_case_									=				{}
										for col_id, (k, v) in enumerate(features.items()	):
															if isinstance(__UpperCAmelCase,      _ArrayXD	):
																				snake_case_									=				np.random.rand(*v.shape	).astype(v.dtype	)
															elif isinstance(__UpperCAmelCase,      datasets.Value	):
																				if v.dtype == "string":
																									snake_case_									=				'''The small grey turtle was surprisingly fast when challenged.'''
																				else:
																									snake_case_									=				np.random.randint(10,      size=1	).astype(v.dtype	).item()
															elif isinstance(__UpperCAmelCase,      datasets.Sequence	):
																				while isinstance(__UpperCAmelCase,      datasets.Sequence	):
																									snake_case_									=				v.feature
																				snake_case_									=				seq_shapes[k]
																				snake_case_									=				np.random.rand(*__UpperCAmelCase	).astype(v.dtype	)
															snake_case_									=				data

										dummy_data.append((i, example)	)

					return dummy_data


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase=100,      __UpperCAmelCase=None	)		->					Optional[Any]:

					'''simple docstring'''

					snake_case_									=				generate_examples(__UpperCAmelCase,      num_examples=__UpperCAmelCase,      seq_shapes=__UpperCAmelCase	)

					with ArrowWriter(features=__UpperCAmelCase,      path=__UpperCAmelCase	) as writer:
										for key, record in dummy_data:
															snake_case_									=				features.encode_example(__UpperCAmelCase	)
															writer.write(__UpperCAmelCase	)

										snake_case_			,snake_case_									=				writer.finalize()

					if not num_final_examples == num_examples:
										raise ValueError(
										    F"Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."	)

					snake_case_									=				datasets.Dataset.from_file(filename=__UpperCAmelCase,      info=datasets.DatasetInfo(features=__UpperCAmelCase	)	)

					return dataset







'''simple docstring'''

import math
from collections.abc import Callable


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase	)		->					float:

					'''simple docstring'''

					snake_case_									=				xa
					snake_case_									=				xa
					while True:
										if x_n == x_na or function(__UpperCAmelCase	) == function(__UpperCAmelCase	):
															raise ZeroDivisionError('''float division by zero, could not find root'''	)
										snake_case_									=				x_na - (
										    function(__UpperCAmelCase	) / ((function(__UpperCAmelCase	) - function(__UpperCAmelCase	)) / (x_na - x_n))
										)
										if abs(x_na - x_na	) < 10**-5:
															return x_na
										snake_case_									=				x_na
										snake_case_									=				x_na


def 		__magic_name__    (	__UpperCAmelCase	)		->					float:

					'''simple docstring'''

					return math.pow(__UpperCAmelCase,      3	) - (2 * x) - 5


if __name__ == "__main__":
							print(intersection(f, 3, 3.5))

