import unittest

from transformers.utils.backbone_utils import (
    BackboneMixin,
    get_aligned_output_features_output_indices,
    verify_out_features_out_indices,
)




class 	__snake_case	( unittest.TestCase		):





      '''simple docstring'''






      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->Optional[Any]:


          """simple docstring"""


          _lowerCamelCase     :		Tuple 						=						["""a""", """b""", """c"""]

          # Defaults to last layer if both are None
          _lowerCamelCase     :		int 						=						get_aligned_output_features_output_indices(_UpperCamelCase    ,  _UpperCamelCase    ,  _UpperCamelCase)
          self.assertEqual(_UpperCamelCase    ,  ["""c"""])
          self.assertEqual(_UpperCamelCase    ,  [2])

          # Out indices set to match out features
          _lowerCamelCase     :		int 						=						get_aligned_output_features_output_indices(["""a""", """c"""]    ,  _UpperCamelCase    ,  _UpperCamelCase)
          self.assertEqual(_UpperCamelCase    ,  ["""a""", """c"""])
          self.assertEqual(_UpperCamelCase    ,  [0, 2])

          # Out features set to match out indices
          _lowerCamelCase     :		Tuple 						=						get_aligned_output_features_output_indices(_UpperCamelCase    ,  [0, 2]    ,  _UpperCamelCase)
          self.assertEqual(_UpperCamelCase    ,  ["""a""", """c"""])
          self.assertEqual(_UpperCamelCase    ,  [0, 2])

          # Out features selected from negative indices
          _lowerCamelCase     :		str 						=						get_aligned_output_features_output_indices(_UpperCamelCase    ,  [-3, -1]    ,  _UpperCamelCase)
          self.assertEqual(_UpperCamelCase    ,  ["""a""", """c"""])
          self.assertEqual(_UpperCamelCase    ,  [-3, -1])



      def 	_SCREAMING_SNAKE_CASE    (					self     :				int)				->int:


          """simple docstring"""


          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(["""a""", """b"""]    ,  (0, 1)    ,  _UpperCamelCase)

          # Out features must be a list
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(("""a""", """b""")    ,  (0, 1)    ,  ["""a""", """b"""])

          # Out features must be a subset of stage names
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(["""a""", """b"""]    ,  (0, 1)    ,  ["""a"""])

          # Out indices must be a list or tuple
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(_UpperCamelCase    ,  0    ,  ["""a""", """b"""])

          # Out indices must be a subset of stage names
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(_UpperCamelCase    ,  (0, 1)    ,  ["""a"""])

          # Out features and out indices must be the same length
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(["""a""", """b"""]    ,  (0,)    ,  ["""a""", """b""", """c"""])

          # Out features should match out indices
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(["""a""", """b"""]    ,  (0, 2)    ,  ["""a""", """b""", """c"""])

          # Out features and out indices should be in order
          with self.assertRaises(_UpperCamelCase):
              verify_out_features_out_indices(["""b""", """a"""]    ,  (0, 1)    ,  ["""a""", """b"""])

          # Check passes with valid inputs
          verify_out_features_out_indices(["""a""", """b""", """d"""]    ,  (0, 1, -1)    ,  ["""a""", """b""", """c""", """d"""])




      def 	_SCREAMING_SNAKE_CASE    (					self     :				int)				->List[Any]:


          """simple docstring"""


          _lowerCamelCase     :		int 						=						BackboneMixin()

          _lowerCamelCase     :		Union[str, Any] 						=						["""a""", """b""", """c"""]
          _lowerCamelCase     :		Tuple 						=						["""a""", """c"""]
          _lowerCamelCase     :		List[Any] 						=						[0, 2]

          # Check that the output features and indices are set correctly
          self.assertEqual(backbone.out_features    ,  ["""a""", """c"""])
          self.assertEqual(backbone.out_indices    ,  [0, 2])

          # Check out features and indices are updated correctly
          _lowerCamelCase     :		str 						=						["""a""", """b"""]
          self.assertEqual(backbone.out_features    ,  ["""a""", """b"""])
          self.assertEqual(backbone.out_indices    ,  [0, 1])

          _lowerCamelCase     :		Optional[int] 						=						[-3, -1]
          self.assertEqual(backbone.out_features    ,  ["""a""", """c"""])
          self.assertEqual(backbone.out_indices    ,  [-3, -1])





import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		Optional[int] 						=						ArgumentParser(
        description=(
            """PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"""
        )	)

    # Optional arguments for the launch helper
    parser.add_argument("""--num_cores"""   , type=__A   , default=1   , help="""Number of TPU cores to use (1 or 8)."""	)

    # positional
    parser.add_argument(
        """training_script"""   , type=__A   , help=(
            """The full path to the single TPU training """
            """program/script to be launched in parallel, """
            """followed by all the arguments for the """
            """training script"""
        )   , )

    # rest from the training program
    parser.add_argument("""training_script_args"""   , nargs=__A	)

    return parser.parse_args()







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		List[str] 						=						parse_args()

    # Import training_script as a module.
    _lowerCamelCase     :		List[Any] 						=						Path(args.training_script	)
    sys.path.append(str(script_fpath.parent.resolve()	)	)
    _lowerCamelCase     :		Optional[Any] 						=						script_fpath.stem
    _lowerCamelCase     :		Dict 						=						importlib.import_module(__A	)

    # Patch sys.argv
    _lowerCamelCase     :		Union[str, Any] 						=						[args.training_script] + args.training_script_args + ["""--tpu_num_cores""", str(args.num_cores	)]

    xmp.spawn(mod._mp_fn   , args=()   , nprocs=args.num_cores	)


if __name__ == "__main__":
    main()




