




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


lowerCAmelCase_					    = logging.get_logger(__name__)

lowerCAmelCase_					    = {
    '''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      ,				__UpperCAmelCase=None      ,				**__UpperCAmelCase		):
        logger.info('''`diffusers.OnnxRuntimeModel` is experimental and might change in the future.'''		)
        lowerCAmelCase__				:  Tuple		       =     model
        lowerCAmelCase__				:  List[str]		       =     kwargs.get('''model_save_dir'''      ,				_A		)
        lowerCAmelCase__				:  Any		       =     kwargs.get('''latest_model_name'''      ,				_A		)

      def __call__(   self      ,				**__UpperCAmelCase		):
        lowerCAmelCase__				:  Union[str, Any]		       =     {k: np.array(_A		) for k, v in kwargs.items()}
        return self.model.run(_A      ,				_A		)

      @staticmethod
      def 	__magic_name__(   __UpperCAmelCase      ,				__UpperCAmelCase=None      ,				__UpperCAmelCase=None		):
        if provider is None:
          logger.info('''No onnxruntime provider specified, using CPUExecutionProvider'''		)
          lowerCAmelCase__				:  List[Any]		       =     'CPUExecutionProvider'

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

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase = None      ,				**__UpperCAmelCase		):
        lowerCAmelCase__				:  Optional[Any]		       =     file_name if file_name is not None else ONNX_WEIGHTS_NAME

        lowerCAmelCase__				:  Union[str, Any]		       =     self.model_save_dir.joinpath(self.latest_model_name		)
        lowerCAmelCase__				:  List[Any]		       =     Path(_A		).joinpath(_A		)
        try:
          shutil.copyfile(_A      ,				_A		)
        except shutil.SameFileError:
          pass

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

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				**__UpperCAmelCase      ,				):
        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 	__magic_name__(   cls      ,				__UpperCAmelCase      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = False      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = None      ,				**__UpperCAmelCase      ,				):
        lowerCAmelCase__				:  str		       =     file_name if file_name is not None else ONNX_WEIGHTS_NAME
        # load model from local directory
        if os.path.isdir(_A		):
          lowerCAmelCase__				:  Tuple		       =     OnnxRuntimeModel.load_model(
              os.path.join(_A      ,				_A		)      ,				provider=_A      ,				sess_options=_A		)
          lowerCAmelCase__				:  Any		       =     Path(_A		)
        # load model from hub
        else:
          # download model
          lowerCAmelCase__				:  Tuple		       =     hf_hub_download(
              repo_id=_A      ,				filename=_A      ,				use_auth_token=_A      ,				revision=_A      ,				cache_dir=_A      ,				force_download=_A      ,				)
          lowerCAmelCase__				:  str		       =     Path(_A		).parent
          lowerCAmelCase__				:  Tuple		       =     Path(_A		).name
          lowerCAmelCase__				:  Tuple		       =     OnnxRuntimeModel.load_model(_A      ,				provider=_A      ,				sess_options=_A		)
        return cls(model=_A      ,				**_A		)







      @classmethod
      def 	__magic_name__(   cls      ,				__UpperCAmelCase      ,				__UpperCAmelCase = True      ,				__UpperCAmelCase = None      ,				__UpperCAmelCase = None      ,				**__UpperCAmelCase      ,				):
        lowerCAmelCase__				:  Union[str, Any]		       =     None
        if len(str(_A		).split('''@'''		)		) == 2:
          lowerCAmelCase__				:  Optional[Any]		       =     model_id.split('''@'''		)

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







def      __lowerCAmelCase			(					UpperCamelCase      )     ->	bool:
  if not isinstance(UpperCamelCase	,      UpperCamelCase      ):
    raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''      )
  if len(UpperCamelCase      ) == 0:
    raise ValueError('''Input list must be a non empty list'''      )
  if len(UpperCamelCase      ) == 1:
    return True
  lowerCAmelCase__				:  Tuple		       =     series[1] - series[0]
  for index in range(len(UpperCamelCase      ) - 1      ):
    if series[index + 1] - series[index] != common_diff:
      return False
  return True



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	float:
  if not isinstance(UpperCamelCase	,      UpperCamelCase      ):
    raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''      )
  if len(UpperCamelCase      ) == 0:
    raise ValueError('''Input list must be a non empty list'''      )
  lowerCAmelCase__				:  int		       =     0
  for val in series:
    answer += val
  return answer / len(UpperCamelCase      )


if __name__ == "__main__":
     import doctest

     doctest.testmod()

