

'''simple docstring'''

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      :			List[str]    ,   __lowercase      :			str=None    ,   **__lowercase      :			Dict   ):







            """simple docstring"""







            logger.info('`diffusers.OnnxRuntimeModel` is experimental and might change in the future.'   )
            __lowercase      		=model
            __lowercase      		=kwargs.get('model_save_dir'    ,   __lowercase   )
            __lowercase      		=kwargs.get('latest_model_name'    ,   __lowercase   )







       def __call__(				self      :			List[str]    ,   **__lowercase      :			int   ):







            """simple docstring"""







            __lowercase      		={k: np.array(__lowercase   ) for k, v in kwargs.items()}
            return self.model.run(__lowercase    ,   __lowercase   )







       @staticmethod
       def       snake_case (				__lowercase      :			Union[str, Path]    ,   __lowercase      :			List[Any]=None    ,   __lowercase      :			Optional[Any]=None   ):







            """simple docstring"""







            if provider is None:
                 logger.info('No onnxruntime provider specified, using CPUExecutionProvider'   )
                 __lowercase      		='CPUExecutionProvider'

            return ort.InferenceSession(__lowercase    ,   providers=[provider]    ,   sess_options=__lowercase   )







       def       snake_case (				self      :			Dict    ,   __lowercase      :			Union[str, Path]    ,   __lowercase      :			Optional[str] = None    ,   **__lowercase      :			List[Any]   ):







            """simple docstring"""







            __lowercase      		=file_name if file_name is not None else ONNX_WEIGHTS_NAME

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

            # copy external weights (for models >2GB)
            __lowercase      		=self.model_save_dir.joinpath(__lowercase   )
            if src_path.exists():
                 __lowercase      		=Path(__lowercase   ).joinpath(__lowercase   )
                 try:
                      shutil.copyfile(__lowercase    ,   __lowercase   )
                 except shutil.SameFileError:
                      pass







       def       snake_case (				self      :			List[Any]    ,   __lowercase      :			Union[str, os.PathLike]    ,   **__lowercase      :			Any    ,   ):







            """simple docstring"""







            if os.path.isfile(__lowercase   ):
                 logger.error(f'''Provided path ({save_directory}) should be a directory, not a file'''   )
                 return

            os.makedirs(__lowercase    ,   exist_ok=__lowercase   )

            # saving model weights/files
            self._save_pretrained(__lowercase    ,   **__lowercase   )







       @classmethod
       def       snake_case (				cls      :			Any    ,   __lowercase      :			Union[str, Path]    ,   __lowercase      :			Optional[Union[bool, str, None]] = None    ,   __lowercase      :			Optional[Union[str, None]] = None    ,   __lowercase      :			bool = False    ,   __lowercase      :			Optional[str] = None    ,   __lowercase      :			Optional[str] = None    ,   __lowercase      :			Optional[str] = None    ,   __lowercase      :			Optional["ort.SessionOptions"] = None    ,   **__lowercase      :			Tuple    ,   ):







            """simple docstring"""







            __lowercase      		=file_name if file_name is not None else ONNX_WEIGHTS_NAME
            # load model from local directory
            if os.path.isdir(__lowercase   ):
                 __lowercase      		=OnnxRuntimeModel.load_model(
                     os.path.join(__lowercase    ,   __lowercase   )    ,   provider=__lowercase    ,   sess_options=__lowercase   )
                 __lowercase      		=Path(__lowercase   )
            # load model from hub
            else:
                 # download model
                 __lowercase      		=hf_hub_download(
                     repo_id=__lowercase    ,   filename=__lowercase    ,   use_auth_token=__lowercase    ,   revision=__lowercase    ,   cache_dir=__lowercase    ,   force_download=__lowercase    ,   )
                 __lowercase      		=Path(__lowercase   ).parent
                 __lowercase      		=Path(__lowercase   ).name
                 __lowercase      		=OnnxRuntimeModel.load_model(__lowercase    ,   provider=__lowercase    ,   sess_options=__lowercase   )
            return cls(model=__lowercase    ,   **__lowercase   )







       @classmethod
       def       snake_case (				cls      :			int    ,   __lowercase      :			Union[str, Path]    ,   __lowercase      :			bool = True    ,   __lowercase      :			Optional[str] = None    ,   __lowercase      :			Optional[str] = None    ,   **__lowercase      :			Optional[Any]    ,   ):







            """simple docstring"""







            __lowercase      		=None
            if len(str(__lowercase   ).split('@'   )   ) == 2:
                 __lowercase		,  __lowercase      		=model_id.split('@'   )

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





'''simple docstring'''

def 					__UpperCamelCase				(						lowercase__    :	List[str],       lowercase__    :	Tuple			):






     '''simple docstring'''





     __lowercase      		=[0 for i in range(r + 1			)]
     # nc0 = 1
     __lowercase      		=1
     for i in range(1,       n + 1			):
          # to compute current row from previous row.
          __lowercase      		=min(lowercase__,       lowercase__			)
          while j > 0:
               c[j] += c[j - 1]
               j -= 1
     return c[r]







print(binomial_coefficient(n=10, r=5))


