


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


A :	int												=     get_logger(__name__)






def 				UpperCamelCase      (			__magic_name__  :							List[str]  )     ->						Optional[int]:
  """simple docstring"""




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





from __future__ import annotations






def 				UpperCamelCase      (			__magic_name__  :							list[list[int]]					,					__magic_name__  :							list[list[int]]  )     ->						list[int]:
		"""simple docstring"""




		assert len(__magic_name__  ) == len(__magic_name__  )

		lowercase__      =	len(__magic_name__  )
		lowercase__      =	list(range(__magic_name__  )  )
		lowercase__      =	[-1] * n  # who the donor has donated to
		lowercase__      =	[-1] * n  # who the recipient has received from
		lowercase__      =	[0] * n

		while unmatched_donors:
				lowercase__      =	unmatched_donors[0]
				lowercase__      =	donor_pref[donor]
				lowercase__      =	donor_preference[num_donations[donor]]
				num_donations[donor] += 1
				lowercase__      =	recipient_pref[recipient]
				lowercase__      =	rec_record[recipient]

				if prev_donor != -1:
						if rec_preference.index(__magic_name__  ) > rec_preference.index(__magic_name__  ):
								lowercase__      =	donor
								lowercase__      =	recipient
								unmatched_donors.append(__magic_name__  )
								unmatched_donors.remove(__magic_name__  )
				else:
						lowercase__      =	donor
						lowercase__      =	recipient
						unmatched_donors.remove(__magic_name__  )
		return donor_record

