



'''simple docstring'''




def      a      (			lowerCamelCase__						,				lowerCamelCase__						,				lowerCamelCase__						,				lowerCamelCase__						,				lowerCamelCase__						,				):
			'''simple docstring'''





			A_     :						List[Any]     =					[redshift, radiation_density, matter_density, dark_energy]
			if any(p < 0 for p in parameters   ):
						raise ValueError("""All input parameters must be positive"""   )

			if any(p > 1 for p in parameters[1:4]   ):
						raise ValueError("""Relative densities cannot be greater than one"""   )
			else:
						A_     :						Tuple     =					1 - (matter_density + radiation_density + dark_energy)

						A_     :						Any     =					(
						    radiation_density * (redshift + 1) ** 4
						    + matter_density * (redshift + 1) ** 3
						    + curvature * (redshift + 1) ** 2
						    + dark_energy
						)

						A_     :						List[str]     =					hubble_constant * e_a ** (1 / 2)
						return hubble


if __name__ == "__main__":
						import doctest

						# run doctest
						doctest.testmod()

						# demo LCDM approximation
						lowerCamelCase							:Tuple       = 0.3

						print(
						    hubble_parameter(
						        hubble_constant=68.3,
						        radiation_density=1E-4,
						        matter_density=matter_density,
						        dark_energy=1 - matter_density,
						        redshift=0,
						    )
						)




'''simple docstring'''




import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad







class      _lowerCAmelCase							(      unittest.TestCase			):


	def    _a     (self							):
				A_     :						Dict     =					10


	def    _a     (self							):
				A_     :						str     =					[1, 2, 3, 4]
				A_     :						List[str]     =					[1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						str     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				A_     :						Tuple     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						List[Any]     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
				A_     :						str     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						Any     =					"""It was the year of Our Lord one thousand seven hundred and
        seventy-five.\n\nSpiritual revelations were conceded to England at that
        favoured period, as at this."""
				A_,   A_     :						Optional[int]     =					process_story(lowercase							)
				self.assertEqual(lowercase	,				[]							)


	def    _a     (self							):
				A_     :						Union[str, Any]     =					""""""
				A_,   A_     :						Union[str, Any]     =					process_story(lowercase							)
				self.assertEqual(lowercase	,				[]							)
				self.assertEqual(lowercase	,				[]							)


	def    _a     (self							):
				A_     :						List[Any]     =					(
				    """It was the year of Our Lord one thousand seven hundred and """
				    """seventy-five\n\nSpiritual revelations were conceded to England """
				    """at that favoured period, as at this.\n@highlight\n\nIt was the best of times"""
				)
				A_,   A_     :						int     =					process_story(lowercase							)

				A_     :						List[Any]     =					[
				    """It was the year of Our Lord one thousand seven hundred and seventy-five.""",
				    """Spiritual revelations were conceded to England at that favoured period, as at this.""",
				]
				self.assertEqual(lowercase	,				lowercase							)

				A_     :						Tuple     =					["""It was the best of times."""]
				self.assertEqual(lowercase	,				lowercase							)


	def    _a     (self							):
				A_     :						Dict     =					torch.tensor([1, 2, 3, 4]							)
				A_     :						Union[str, Any]     =					torch.tensor([1, 1, 1, 1]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				0							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						Union[str, Any]     =					torch.tensor([1, 2, 3, 4, 23, 23, 23]							)
				A_     :						List[str]     =					torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				23							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						Optional[Any]     =					torch.tensor([8, 2, 3, 4, 1, 1, 1]							)
				A_     :						Tuple     =					torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				1							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						List[str]     =					101
				A_     :						str     =					torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 101, 5, 6], [1, 101, 3, 4, 101, 6]]							)
				A_     :						int     =					torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]							)

				A_     :						Optional[Any]     =					compute_token_type_ids(lowercase	,				lowercase							)
				np.testing.assert_array_equal(lowercase	,				lowercase							)