'''simple docstring'''

def 				UpperCamelCase__      (      a__      ,   a__      ,   a__      ,   a__   ):


						'''simple docstring'''






						if start == end:
												return start if lst[start] > item else start + 1
						if start > end:
												return start

						_lowerCAmelCase					    =(start + end) // 2
						if lst[mid] < item:
												return binary_search(a__      ,   a__      ,   mid + 1      ,   a__   )
						elif lst[mid] > item:
												return binary_search(a__      ,   a__      ,   a__      ,   mid - 1   )
						else:
												return mid



def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =len(a__   )

						for index in range(1      ,   a__   ):
												_lowerCAmelCase					    =lst[index]
												_lowerCAmelCase					    =binary_search(a__      ,   a__      ,   0      ,   index - 1   )
												_lowerCAmelCase					    =lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

						return lst



def 				UpperCamelCase__      (      a__      ,   a__   ):


						'''simple docstring'''






						if not left:
												return right

						if not right:
												return left

						if left[0] < right[0]:
												return [left[0], *merge(left[1:]      ,   a__   )]

						return [right[0], *merge(a__      ,   right[1:]   )]



def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =len(a__   )
						_lowerCAmelCase					    =[], []
						_lowerCAmelCase					    =[lst[0]]
						_lowerCAmelCase					    =[]
						_lowerCAmelCase					    =1
						while i < length:
												if lst[i] < lst[i - 1]:
																		runs.append(a__   )
																		_lowerCAmelCase					    =[lst[i]]
												else:
																		new_run.append(lst[i]   )
												i += 1
						runs.append(a__   )

						for run in runs:
												sorted_runs.append(insertion_sort(a__   )   )
						for run in sorted_runs:
												_lowerCAmelCase					    =merge(a__      ,   a__   )

						return sorted_array



def 				UpperCamelCase__      (      ):


						'''simple docstring'''






						_lowerCAmelCase					    =[5, 9, 1_0, 3, -4, 5, 1_7_8, 9_2, 4_6, -1_8, 0, 7]
						_lowerCAmelCase					    =tim_sort(a__   )
						print(a__   )


if __name__ == "__main__":
							main()











'''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


lowercase						:   Tuple      						=							get_logger(__name__)




def 		a_(			lowerCamelCase   )					->Any:






       '''simple docstring'''




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




