





from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments






def 					lowerCamelCase_						(    )		->						str:






				"""simple docstring"""


				snake_case_						:   Dict           =  HfArgumentParser(_UpperCamelCase			)
				snake_case_						:   Any           =  parser.parse_args_into_dataclasses()[0]
				snake_case_						:   Union[str, Any]           =  TensorFlowBenchmark(args=_UpperCamelCase			)
				try:
								snake_case_						:   List[str]           =  parser.parse_args_into_dataclasses()[0]
				except ValueError as e:
								snake_case_						:   Any           =  '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
								snake_case_						:   Optional[Any]           =  ''' '''.join(str(_UpperCamelCase			).split(''' '''			)[:-1]			)
								snake_case_						:   List[str]           =  ''''''
								snake_case_						:   List[str]           =  eval(str(_UpperCamelCase			).split(''' '''			)[-1]			)
								snake_case_						:   Dict           =  []
								for arg in depreciated_args:
												# arg[2:] removes '--'
												if arg[2:] in TensorFlowBenchmark.deprecated_args:
																# arg[5:] removes '--no_'
																full_error_msg += arg_error_msg.format(arg[5:]			)
												else:
																wrong_args.append(_UpperCamelCase			)
								if len(_UpperCamelCase			) > 0:
												snake_case_						:   List[Any]           =  full_error_msg + begin_error_msg + str(_UpperCamelCase			)
								raise ValueError(_UpperCamelCase			)
				benchmark.run()


if __name__ == "__main__":
	main()







import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
	import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin



@require_torch
class  __lowerCAmelCase	(      unittest.TestCase,					_a					):






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   Dict           =  load_tool('''text-to-speech'''   )
							self.tool.setup()






			def       lowerCamelCase  (self   )					->       List[str]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Optional[int]           =  self.tool('''hey'''   )
							snake_case_						:   Union[str, Any]           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Any           =  self.tool('''hey'''   )
							snake_case_						:   str           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )
