'''simple docstring'''




import os

from packaging import version

from .. import __version__
from .accelerate_utils import apply_forward_hook
from .constants import (
    CONFIG_NAME,
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    DIFFUSERS_DYNAMIC_MODULE_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    ONNX_EXTERNAL_WEIGHTS_NAME,
    ONNX_WEIGHTS_NAME,
    SAFETENSORS_WEIGHTS_NAME,
    TEXT_ENCODER_ATTN_MODULE,
    WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import (
    HF_HUB_OFFLINE,
    _add_variant,
    _get_model_file,
    extract_commit_hash,
    http_user_agent,
)
from .import_utils import (
    BACKENDS_MAPPING,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    is_accelerate_available,
    is_accelerate_version,
    is_bsa_available,
    is_flax_available,
    is_ftfy_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_omegaconf_available,
    is_onnx_available,
    is_safetensors_available,
    is_scipy_available,
    is_tensorboard_available,
    is_tf_available,
    is_torch_available,
    is_torch_version,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    is_wandb_available,
    is_xformers_available,
    requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION, numpy_to_pil, pt_to_pil
from .torch_utils import is_compiled_module, randn_tensor


if is_torch_available():
  from .testing_utils import (
      floats_tensor,
      load_hf_numpy,
      load_image,
      load_numpy,
      load_pt,
      nightly,
      parse_flag_from_env,
      print_tensor_test,
      require_torch_a,
      require_torch_gpu,
      skip_mps,
      slow,
      torch_all_close,
      torch_device,
  )
  from .torch_utils import maybe_allow_in_graph

from .testing_utils import export_to_gif, export_to_video


__snake_case   :      List[Any]						    =  get_logger(__name__)





def      _UpperCAmelCase    (							_UpperCamelCase    :	Dict   )	->      Any:
    if version.parse(_UpperCamelCase   ) < version.parse(_UpperCamelCase   ):
        if "dev" in min_version:
            A_     =   (
                '''This example requires a source install from HuggingFace diffusers (see '''
                '''`https://huggingface.co/docs/diffusers/installation#install-from-source`),'''
            )
        else:
            A_     =   F'''This example requires a minimum version of {min_version},'''
        error_message += F''' but the version found is {__version__}.\n'''
        raise ImportError(_UpperCamelCase   )









from itertools import permutations


def     _UpperCAmelCase				(     ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_													=  list(map(''.join       ,      permutations('0123456789'				)				)				)
    return result[999_999]


if __name__ == "__main__":
       print(solution())


