



"""simple docstring"""






import timeit

import numpy as np

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


def 			_lowercase				(  __snake_case	)						->   List[str]:
			def wrapper(*__snake_case					,**__snake_case	):
						__lowerCAmelCase      :  Dict												=       timeit.default_timer()
						__lowerCAmelCase      :  int												=       func(*__snake_case					,**__snake_case	)
						__lowerCAmelCase      :  int												=       timeit.default_timer() - starttime
						return delta

			__lowerCAmelCase      :  Union[str, Any]												=       func.__name__

			return wrapper


def 			_lowercase				(  __snake_case					,__snake_case=100					,__snake_case=None	)						->   int:
			__lowerCAmelCase      :  Optional[int]												=       []
			__lowerCAmelCase      :  Dict												=       seq_shapes or {}
			for i in range(__snake_case	):
						__lowerCAmelCase      :  Dict												=       {}
						for col_id, (k, v) in enumerate(features.items()	):
									if isinstance(__snake_case					,_ArrayXD	):
												__lowerCAmelCase      :  Any												=       np.random.rand(*v.shape	).astype(v.dtype	)
									elif isinstance(__snake_case					,datasets.Value	):
												if v.dtype == "string":
															__lowerCAmelCase      :  Optional[Any]												=       "The small grey turtle was surprisingly fast when challenged."
												else:
															__lowerCAmelCase      :  Optional[int]												=       np.random.randint(10					,size=1	).astype(v.dtype	).item()
									elif isinstance(__snake_case					,datasets.Sequence	):
												while isinstance(__snake_case					,datasets.Sequence	):
															__lowerCAmelCase      :  Dict												=       v.feature
												__lowerCAmelCase      :  Union[str, Any]												=       seq_shapes[k]
												__lowerCAmelCase      :  List[Any]												=       np.random.rand(*__snake_case	).astype(v.dtype	)
									__lowerCAmelCase      :  str												=       data

						dummy_data.append((i, example)	)

			return dummy_data





def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case=100					,__snake_case=None	)						->   Optional[int]:
			__lowerCAmelCase      :  Union[str, Any]												=       generate_examples(__snake_case					,num_examples=__snake_case					,seq_shapes=__snake_case	)

			with ArrowWriter(features=__snake_case					,path=__snake_case	) as writer:
						for key, record in dummy_data:
									__lowerCAmelCase      :  List[str]												=       features.encode_example(__snake_case	)
									writer.write(__snake_case	)

						__lowerCAmelCase						,	__lowerCAmelCase      :  Dict												=       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}."""	)

			__lowerCAmelCase      :  Optional[int]												=       datasets.Dataset.from_file(filename=__snake_case					,info=datasets.DatasetInfo(features=__snake_case	)	)

			return dataset




"""simple docstring"""






def 			_lowercase				(  __snake_case					,__snake_case	)						->   float:
			if digit_amount > 0:
						return round(number - int(__snake_case	)					,__snake_case	)
			return number - int(__snake_case	)


if __name__ == "__main__":
	print(decimal_isolate(1.53, 0))
	print(decimal_isolate(35.345, 1))
	print(decimal_isolate(35.345, 2))
	print(decimal_isolate(35.345, 3))
	print(decimal_isolate(-14.789, 3))
	print(decimal_isolate(0, 2))
	print(decimal_isolate(-14.123, 1))
	print(decimal_isolate(-14.123, 2))
	print(decimal_isolate(-14.123, 3))