


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        snake_case__	(			unittest.TestCase							):





	def      A					(	self				)		->      List[str]:
								"""simple docstring"""






								a_							: List[str]								=						torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
								a_							: int								=						get_activation("""gelu"""				)
								self.assertTrue(torch.allclose(gelu_python(UpperCamelCase_				)					,     torch_builtin(UpperCamelCase_				)				)				)
								self.assertFalse(torch.allclose(gelu_python(UpperCamelCase_				)					,     gelu_new(UpperCamelCase_				)				)				)





	def      A					(	self				)		->      Dict:
								"""simple docstring"""






								a_							: int								=						torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
								a_							: Union[str, Any]								=						get_activation("""gelu"""				)
								a_							: Tuple								=						get_activation("""gelu_10"""				)

								a_							: Union[str, Any]								=						torch_builtin(UpperCamelCase_				)
								a_							: Dict								=						geluaa(UpperCamelCase_				)

								a_							: Optional[Any]								=						torch.where(y_gelu_aa < 10.0					,     1					,     0				)

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





	def      A					(	self				)		->      Optional[Any]:
								"""simple docstring"""






								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(UpperCamelCase_				):
															get_activation("""bogus"""				)
								with self.assertRaises(UpperCamelCase_				):
															get_activation(UpperCamelCase_				)





	def      A					(	self				)		->      Tuple:
								"""simple docstring"""






								a_							: str								=						get_activation("""gelu"""				)
								a_							: Optional[Any]								=						1
								a_							: Union[str, Any]								=						get_activation("""gelu"""				)
								self.assertEqual(acta.a					,     1				)
								with self.assertRaises(UpperCamelCase_				):
															a_							: Tuple								=						acta.a






'''simple docstring'''
import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment
@require_huggingface_suite
class   lowercase      (				unittest.TestCase   ):

		"""simple docstring"""

		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :Any				   =					inspect.getfile(accelerate.test_utils				)
							UpperCamelCase__  :Any				   =					os.path.sep.join(
							    mod_file.split(os.path.sep				)[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']				)

							from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

							UpperCamelCase__  :List[str]				   =					test_metrics




		@require_cpu
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							debug_launcher(self.test_metrics.main       ,  num_processes=1				)




		@require_cpu
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							debug_launcher(self.test_metrics.main				)




		@require_single_gpu
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							self.test_metrics.main()




		@require_multi_gpu
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							print(F'''Found {torch.cuda.device_count()} devices.'''				)
							UpperCamelCase__  :Optional[Any]				   =					['''torchrun''', F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
							with patch_environment(omp_num_threads=1				):
												execute_subprocess_async(UpperCamelCase_       ,  env=os.environ.copy()				)