






"""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


UpperCamelCase											=     get_logger(__name__)






def 							lowerCAmelCase			(   UpperCamelCase_:				Union[str, Any]       )							->				Tuple:







  '''simple docstring'''







  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_       )










"""simple docstring"""




from __future__ import annotations






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				int       )							->				tuple[float, float]:







  '''simple docstring'''







  assert (
      c % greatest_common_divisor(UpperCamelCase_  ,			UpperCamelCase_       ) == 0
  )  # greatest_common_divisor(a,b) function implemented below
  ((_a)      ,						(_a)      ,						(_a))					      =						extended_gcd(UpperCamelCase_  ,			UpperCamelCase_       )  # extended_gcd(a,b) function implemented below
  _a					      =						c / d
  return (r * x, r * y)






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				int = 2       )							->				None:







  '''simple docstring'''







  ((_a)      ,						(_a))					      =						diophantine(UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_       )  # Initial value
  _a					      =						greatest_common_divisor(UpperCamelCase_  ,			UpperCamelCase_       )
  _a					      =						a // d
  _a					      =						b // d

  for i in range(UpperCamelCase_       ):
    _a					      =						xa + i * q
    _a					      =						ya - i * p
    print(UpperCamelCase_  ,			UpperCamelCase_       )






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int       )							->				int:







  '''simple docstring'''







  if a < b:
    _a      ,						_a					      =						b, a

  while a % b != 0:
    _a      ,						_a					      =						b, a % b

  return b






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int       )							->				tuple[int, int, int]:







  '''simple docstring'''







  assert a >= 0 and b >= 0

  if b == 0:
    _a      ,						_a      ,						_a					      =						a, 1, 0
  else:
    ((_a)      ,						(_a)      ,						(_a))					      =						extended_gcd(UpperCamelCase_  ,			a % b       )
    _a					      =						q
    _a					      =						p - q * (a // b)

  assert a % d == 0 and b % d == 0
  assert d == a * x + b * y

  return (d, x, y)


if __name__ == "__main__":
     from doctest import testmod

     testmod(name="""diophantine""", verbose=True)
     testmod(name="""diophantine_all_soln""", verbose=True)
     testmod(name="""extended_gcd""", verbose=True)
     testmod(name="""greatest_common_divisor""", verbose=True)


