






import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
				import torch

				from transformers.activations import gelu_new, gelu_python, get_activation





@require_torch
class 						SCREAMING_SNAKE_CASE				( unittest.TestCase					):





							"""simple docstring"""

							def       __A (  self:   Dict   )    ->				Optional[int]:
												_A								= torch.tensor([-1_00, -1, -0.1, 0, 0.1, 1.0, 1_00]   )
												_A								= get_activation('''gelu'''   )
												self.assertTrue(torch.allclose(gelu_python(_A   )		,     torch_builtin(_A   )   )   )
												self.assertFalse(torch.allclose(gelu_python(_A   )		,     gelu_new(_A   )   )   )

							def       __A (  self:   Optional[int]   )    ->				List[str]:
												_A								= torch.tensor([-1_00, -1, -0.1, 0, 0.1, 1.0, 1_00]   )
												_A								= get_activation('''gelu'''   )
												_A								= get_activation('''gelu_10'''   )

												_A								= torch_builtin(_A   )
												_A								= geluaa(_A   )

												_A								= torch.where(y_gelu_aa < 10.0		,     1		,     0   )

												self.assertTrue(torch.max(_A   ).item() == 10.0   )
												self.assertTrue(torch.allclose(y_gelu * clipped_mask		,     y_gelu_aa * clipped_mask   )   )

							def       __A (  self:   Dict   )    ->				str:
												get_activation('''gelu'''   )
												get_activation('''gelu_10'''   )
												get_activation('''gelu_fast'''   )
												get_activation('''gelu_new'''   )
												get_activation('''gelu_python'''   )
												get_activation('''gelu_pytorch_tanh'''   )
												get_activation('''linear'''   )
												get_activation('''mish'''   )
												get_activation('''quick_gelu'''   )
												get_activation('''relu'''   )
												get_activation('''sigmoid'''   )
												get_activation('''silu'''   )
												get_activation('''swish'''   )
												get_activation('''tanh'''   )
												with self.assertRaises(_A   ):
																	get_activation('''bogus'''   )
												with self.assertRaises(_A   ):
																	get_activation(_A   )



							def       __A (  self:   List[str]   )    ->				Tuple:
												_A								= get_activation('''gelu'''   )
												_A								= 1
												_A								= get_activation('''gelu'''   )
												self.assertEqual(acta.a		,     1   )
												with self.assertRaises(_A   ):
																	_A								= acta.a














def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= word.split()

					def justify(_lowercase					,			_lowercase					,			_lowercase ) -> str:
										_A								= max_width - width
										_A								= len(_lowercase )
										if len(_lowercase ) == 1:
															# if there is only word in line
															# just insert overall_spaces_count for the remainder of line
															return line[0] + " " * overall_spaces_count
										else:
															_A								= words_count - 1
															# num_spaces_between_words_list[i] : tells you to insert
															# num_spaces_between_words_list[i] spaces
															# after word on line[i]
															_A								= spaces_to_insert_between_words * [
															    overall_spaces_count // spaces_to_insert_between_words
															]
															_A								= (
															    overall_spaces_count % spaces_to_insert_between_words
															)
															# distribute spaces via round robin to the left words
															for i in range(_lowercase ):
																				num_spaces_between_words_list[i] += 1
															_A								= []
															for i in range(_lowercase ):
																				# add the word
																				aligned_words_list.append(line[i] )
																				# add the spaces to insert
																				aligned_words_list.append(num_spaces_between_words_list[i] * ''' ''' )
															# just add the last word to the sentence
															aligned_words_list.append(line[-1] )
															# join the aligned words list to form a justified line
															return "".join(_lowercase )

					_A								= []
					_A								= []
					_A								= 0
					for word in words:
										if width + len(_lowercase ) + len(_lowercase ) <= max_width:
															# keep adding words until we can fill out max_width
															# width = sum of length of all words (without overall_spaces_count)
															# len(word) = length of current word
															# len(line) = number of overall_spaces_count to insert between words
															line.append(_lowercase )
															width += len(_lowercase )
										else:
															# justify the line and add it to result
															answer.append(justify(_lowercase					,			_lowercase					,			_lowercase ) )
															# reset new line and new width
															_A							,_A								= [word], len(_lowercase )
					_A								= max_width - width - len(_lowercase )
					answer.append(''' '''.join(_lowercase ) + (remaining_spaces + 1) * ''' ''' )
					return answer


if __name__ == "__main__":
				from doctest import testmod

				testmod()



