


from collections import namedtuple

lowerCamelCase						=		namedtuple('''from_to''', '''from_ to''')

lowerCamelCase						=		{
    """cubicmeter""": from_to(1, 1),
    """litre""": from_to(0.0_0_1, 1000),
    """kilolitre""": from_to(1, 1),
    """gallon""": from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
    """cubicyard""": from_to(0.7_6_4_5_5, 1.3_0_7_9_5),
    """cubicfoot""": from_to(0.0_2_8, 3_5.3_1_4_7),
    """cup""": from_to(0.0_0_0_2_3_6_5_8_8, 4_2_2_6.7_5),
}






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a	):




		"""simple docstring"""






		if from_type not in METRIC_CONVERSION:
				raise ValueError(
				    f'Invalid \'from_type\' value: {from_type!r}  Supported values are:\n'
				    + ''', '''.join(_UpperCAmelCase	)	)
		if to_type not in METRIC_CONVERSION:
				raise ValueError(
				    f'Invalid \'to_type\' value: {to_type!r}.  Supported values are:\n'
				    + ''', '''.join(_UpperCAmelCase	)	)
		return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
		import doctest

		doctest.testmod()








import timeit

import numpy as np

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






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		def wrapper(*_a     ,       **_a	):
				lowerCAmelCase__       :      List[str]   					= timeit.default_timer()
				lowerCAmelCase__       :      List[Any]   					= func(*_a     ,       **_a	)
				lowerCAmelCase__       :      Any   					= timeit.default_timer() - starttime
				return delta

		lowerCAmelCase__       :      Any   					= func.__name__

		return wrapper






def 					lowerCamelCase_   (	_a     ,       _a=100     ,       _a=None	):




		"""simple docstring"""






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

				dummy_data.append((i, example)	)

		return dummy_data






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a=100     ,       _a=None	):




		"""simple docstring"""






		lowerCAmelCase__       :      Optional[Any]   					= generate_examples(_a     ,       num_examples=_a     ,       seq_shapes=_a	)

		with ArrowWriter(features=_a     ,       path=_a	) as writer:
				for key, record in dummy_data:
						lowerCAmelCase__       :      Optional[int]   					= features.encode_example(_a	)
						writer.write(_a	)

				lowerCAmelCase__					,     lowerCAmelCase__       :      List[str]   					= 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__       :      List[Any]   					= datasets.Dataset.from_file(filename=_a     ,       info=datasets.DatasetInfo(features=_a	)	)

		return dataset




