




import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
       import onnxruntime as ort


UpperCAmelCase_									=	logging.get_logger(__name__)

UpperCAmelCase_									=	{
    """tensor(bool)""": np.bool_,
    """tensor(int8)""": np.inta,
    """tensor(uint8)""": np.uinta,
    """tensor(int16)""": np.intaa,
    """tensor(uint16)""": np.uintaa,
    """tensor(int32)""": np.intaa,
    """tensor(uint32)""": np.uintaa,
    """tensor(int64)""": np.intaa,
    """tensor(uint64)""": np.uintaa,
    """tensor(float16)""": np.floataa,
    """tensor(float)""": np.floataa,
    """tensor(double)""": np.floataa,
}





class     lowerCamelCase__:
      def __init__(				self: str    ,       UpperCamelCase_: Union[str, Any]=None    ,       **UpperCamelCase_: Tuple   ):
             logger.info("""`diffusers.OnnxRuntimeModel` is experimental and might change in the future."""   )
             __lowerCamelCase   =						model
             __lowerCamelCase   =						kwargs.get("""model_save_dir"""    ,       _a   )
             __lowerCamelCase   =						kwargs.get("""latest_model_name"""    ,       _a   )
      def __call__(				self: Optional[Any]    ,       **UpperCamelCase_: int   ):
             __lowerCamelCase   =						{k: np.array(_a   ) for k, v in kwargs.items()}
             return self.model.run(_a    ,       _a   )
      @staticmethod
      def 			lowerCAmelCase__						(				UpperCamelCase_: int    ,       UpperCamelCase_: Union[str, Any]=None    ,       UpperCamelCase_: str=None   ):
             if provider is None:
                    logger.info("""No onnxruntime provider specified, using CPUExecutionProvider"""   )
                    __lowerCamelCase   =						"""CPUExecutionProvider"""

             return ort.InferenceSession(_a    ,       providers=[provider]    ,       sess_options=_a   )
      def 			lowerCAmelCase__						(				self: Tuple    ,       UpperCamelCase_: List[Any]    ,       UpperCamelCase_: List[Any] = None    ,       **UpperCamelCase_: str   ):
             __lowerCamelCase   =						file_name if file_name is not None else ONNX_WEIGHTS_NAME

             __lowerCamelCase   =						self.model_save_dir.joinpath(self.latest_model_name   )
             __lowerCamelCase   =						Path(_a   ).joinpath(_a   )
             try:
                    shutil.copyfile(_a    ,       _a   )
             except shutil.SameFileError:
                    pass

             # copy external weights (for models >2GB)
             __lowerCamelCase   =						self.model_save_dir.joinpath(_a   )
             if src_path.exists():
                    __lowerCamelCase   =						Path(_a   ).joinpath(_a   )
                    try:
                           shutil.copyfile(_a    ,       _a   )
                    except shutil.SameFileError:
                           pass
      def 			lowerCAmelCase__						(				self: List[Any]    ,       UpperCamelCase_: Any    ,       **UpperCamelCase_: Any    ,       ):
             if os.path.isfile(_a   ):
                    logger.error(F'Provided path ({save_directory}) should be a directory, not a file'   )
                    return

             os.makedirs(_a    ,       exist_ok=_a   )

             # saving model weights/files
             self._save_pretrained(_a    ,       **_a   )
      @classmethod
      def 			lowerCAmelCase__						(				cls: int    ,       UpperCamelCase_: Optional[int]    ,       UpperCamelCase_: Any = None    ,       UpperCamelCase_: str = None    ,       UpperCamelCase_: str = False    ,       UpperCamelCase_: List[Any] = None    ,       UpperCamelCase_: Tuple = None    ,       UpperCamelCase_: Any = None    ,       UpperCamelCase_: Union[str, Any] = None    ,       **UpperCamelCase_: Any    ,       ):
             __lowerCamelCase   =						file_name if file_name is not None else ONNX_WEIGHTS_NAME
             # load model from local directory
             if os.path.isdir(_a   ):
                    __lowerCamelCase   =						OnnxRuntimeModel.load_model(
                        os.path.join(_a    ,       _a   )    ,       provider=_a    ,       sess_options=_a   )
                    __lowerCamelCase   =						Path(_a   )
             # load model from hub
             else:
                    # download model
                    __lowerCamelCase   =						hf_hub_download(
                        repo_id=_a    ,       filename=_a    ,       use_auth_token=_a    ,       revision=_a    ,       cache_dir=_a    ,       force_download=_a    ,       )
                    __lowerCamelCase   =						Path(_a   ).parent
                    __lowerCamelCase   =						Path(_a   ).name
                    __lowerCamelCase   =						OnnxRuntimeModel.load_model(_a    ,       provider=_a    ,       sess_options=_a   )
             return cls(model=_a    ,       **_a   )




      @classmethod
      def 			lowerCAmelCase__						(				cls: Optional[Any]    ,       UpperCamelCase_: str    ,       UpperCamelCase_: int = True    ,       UpperCamelCase_: Any = None    ,       UpperCamelCase_: int = None    ,       **UpperCamelCase_: List[str]    ,       ):
             __lowerCamelCase   =						None
             if len(str(_a   ).split("""@"""   )   ) == 2:
                    __lowerCamelCase,   __lowerCamelCase   =						model_id.split("""@"""   )

             return cls._from_pretrained(
                 model_id=_a    ,       revision=_a    ,       cache_dir=_a    ,       force_download=_a    ,       use_auth_token=_a    ,       **_a    ,       )







"""simple docstring"""




def     a__ (				snake_case__				)						->					list:

			if len(snake_case__				) < 2:
						return collection

			def circle_sort_util(snake_case__       , snake_case__       , snake_case__				) -> bool:
						lowerCamelCase			      =					False

						if low == high:
									return swapped

						lowerCamelCase			      =					low
						lowerCamelCase			      =					high

						while left < right:
									if collection[left] > collection[right]:
												lowerCamelCase      ,   lowerCamelCase			      =					(
												    collection[right],
												    collection[left],
												)
												lowerCamelCase			      =					True

									left += 1
									right -= 1

						if left == right and collection[left] > collection[right + 1]:
									lowerCamelCase      ,   lowerCamelCase			      =					(
									    collection[right + 1],
									    collection[left],
									)

									lowerCamelCase			      =					True

						lowerCamelCase			      =					low + int((high - low) / 2				)
						lowerCamelCase			      =					circle_sort_util(snake_case__       , snake_case__       , snake_case__				)
						lowerCamelCase			      =					circle_sort_util(snake_case__       , mid + 1       , snake_case__				)

						return swapped or left_swap or right_swap

			lowerCamelCase			      =					True

			while is_not_sorted is True:
						lowerCamelCase			      =					circle_sort_util(snake_case__       , 0       , len(snake_case__				) - 1				)

			return collection


if __name__ == "__main__":
					lowerCAmelCase							:			Tuple     							=							input("""Enter numbers separated by a comma:\n""").strip()
					lowerCAmelCase							:			List[Any]     							=							[int(item) for item in user_input.split(""",""")]
					print(circle_sort(unsorted))



