





"""simple docstring"""


# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async




def 					lowercase__    (					lowercase_=None			)					->		Any:




      """simple docstring"""

      if subparsers is not None:
            _UpperCamelCase      :	Dict						=       subparsers.add_parser("test"			)
      else:
            _UpperCamelCase      :	str						=       argparse.ArgumentParser("Accelerate test command"			)

      parser.add_argument(
          "--config_file"		,default=lowercase_		,help=(
              "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
              "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
              "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
              "with 'huggingface'."
          )		,)

      if subparsers is not None:
            parser.set_defaults(func=lowercase_			)
      return parser




def 					lowercase__    (					lowercase_			)					->		List[Any]:




      """simple docstring"""

      _UpperCamelCase      :	Tuple						=       os.path.sep.join(__file__.split(os.path.sep			)[:-2] + ["test_utils", "scripts", "test_script.py"]			)

      if args.config_file is None:
            _UpperCamelCase      :	int						=       script_name
      else:
            _UpperCamelCase      :	Dict						=       F'''--config_file={args.config_file} {script_name}'''

      _UpperCamelCase      :	str						=       ["accelerate-launch"] + test_args.split()
      _UpperCamelCase      :	Tuple						=       execute_subprocess_async(lowercase_		,env=os.environ.copy()			)
      if result.returncode == 0:
            print("Test is a success! You are ready for your distributed training!"			)




def 					lowercase__    (					)					->		Optional[Any]:




      """simple docstring"""

      _UpperCamelCase      :	int						=       test_command_parser()
      _UpperCamelCase      :	Tuple						=       parser.parse_args()
      test_command(lowercase_			)


if __name__ == "__main__":
  main()







"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase__				  =   {
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   ["Mask2FormerImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   [
      "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "Mask2FormerForUniversalSegmentation",
      "Mask2FormerModel",
      "Mask2FormerPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_maskaformer import MaskaFormerImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_maskaformer import (
        MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        MaskaFormerForUniversalSegmentation,
        MaskaFormerModel,
        MaskaFormerPreTrainedModel,
    )


else:
  import sys

  lowerCamelCase__				  =   _LazyModule(__name__, globals()["__file__"], _import_structure)
