'''simple docstring'''





from pathlib import Path

from .config_args import default_config_file, load_config_from_file
from .config_utils import SubcommandHelpFormatter


a		:  Union[str, Any]   			=			'''Update an existing config file with the latest defaults while maintaining the old configuration.'''





def UpperCAmelCase						(					UpperCAmelCase_	):
    _a							:       Optional[Any]       					=			args.config_file
    if config_file is None and Path(UpperCAmelCase_	).exists():
        _a							:       int       					=			default_config_file
    elif not Path(UpperCAmelCase_	).exists():
        raise ValueError(F'''The passed config file located at {config_file} doesn\'t exist.'''	)
    _a							:       Tuple       					=			load_config_from_file(UpperCAmelCase_	)

    if config_file.endswith(""".json"""	):
        config.to_json_file(UpperCAmelCase_	)
    else:
        config.to_yaml_file(UpperCAmelCase_	)
    return config_file





def UpperCAmelCase						(					UpperCAmelCase_      ,  UpperCAmelCase_	):
    _a							:       Dict       					=			parser.add_parser("""update"""      ,  parents=UpperCAmelCase_      ,  help=UpperCAmelCase_      ,  formatter_class=UpperCAmelCase_	)
    parser.add_argument(
        """--config_file"""      ,  default=UpperCAmelCase_      ,  help=(
            """The path to the config file to update. 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'."""
        )      ,  )

    parser.set_defaults(func=UpperCAmelCase_	)
    return parser





def UpperCAmelCase						(					UpperCAmelCase_	):
    _a							:       Any       					=			update_config(UpperCAmelCase_	)
    print(F'''Sucessfully updated the configuration file at {config_file}.'''	)








'''simple docstring'''





import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference




@slow
@require_torch_gpu
class     UpperCamelCase					(  unittest.TestCase					):



  def 						a_       ( self   ):







      '''simple docstring'''


      _a							:       List[Any]       					=			"""runwayml/stable-diffusion-v1-5"""
      _a							:       Tuple       					=			TextToVideoZeroPipeline.from_pretrained(__lowerCAmelCase		,    torch_dtype=torch.floataa   ).to("""cuda"""   )
      _a							:       Dict       					=			DDIMScheduler.from_config(pipe.scheduler.config   )
      _a							:       int       					=			torch.Generator(device="""cuda"""   ).manual_seed(0   )

      _a							:       Union[str, Any]       					=			"""A bear is playing a guitar on Times Square"""
      _a							:       List[Any]       					=			pipe(prompt=__lowerCAmelCase		,    generator=__lowerCAmelCase   ).images

      _a							:       Any       					=			load_pt(
          """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt"""   )

      assert_mean_pixel_difference(__lowerCAmelCase		,    __lowerCAmelCase   )


