



from __future__ import annotations


def 		_UpperCAmelCase    (				snake_case      ):





					"""simple docstring"""

					if len(snake_case      ) == 0:
										raise ValueError("""find_max() arg is an empty sequence"""      )
					_lowerCAmelCase      =   nums[0]
					for x in nums:
										if x > max_num:
															_lowerCAmelCase      =   x
					return max_num


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)








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__     				=	get_logger(__name__)


def 		_UpperCAmelCase    (				snake_case      ):





					"""simple docstring"""

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



