

"""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


SCREAMING_SNAKE_CASE_     :			Optional[int]	  =			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_     :			Optional[int]	  =			{
    '''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 		_A       :





      def __init__(  self    ,						SCREAMING_SNAKE_CASE__=None    ,						**SCREAMING_SNAKE_CASE__		)   ->					str:
         logger.info("`diffusers.OnnxRuntimeModel` is experimental and might change in the future."		)
         lowerCamelCase__						=			model
         lowerCamelCase__						=			kwargs.get("model_save_dir"    ,						__lowercase		)
         lowerCamelCase__						=			kwargs.get("latest_model_name"    ,						__lowercase		)





      def __call__(  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Union[str, Any]:
         lowerCamelCase__						=			{k: np.array(__lowercase		) for k, v in kwargs.items()}
         return self.model.run(__lowercase    ,						__lowercase		)





      @staticmethod
      def 					_lowerCamelCase  (  SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__=None    ,						SCREAMING_SNAKE_CASE__=None		)   ->					int:
         if provider is None:
            logger.info("No onnxruntime provider specified, using CPUExecutionProvider"		)
            lowerCamelCase__						=			"CPUExecutionProvider"

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





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None    ,						**SCREAMING_SNAKE_CASE__		)   ->					int:
         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(__lowercase		).joinpath(__lowercase		)
         try:
            shutil.copyfile(__lowercase    ,						__lowercase		)
         except shutil.SameFileError:
            pass

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





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					Union[str, Any]:
         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 					_lowerCamelCase  (  cls    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					str:
         lowerCamelCase__						=			file_name if file_name is not None else ONNX_WEIGHTS_NAME
         # load model from local directory
         if os.path.isdir(__lowercase		):
            lowerCamelCase__						=			OnnxRuntimeModel.load_model(
                os.path.join(__lowercase    ,						__lowercase		)    ,						provider=__lowercase    ,						sess_options=__lowercase		)
            lowerCamelCase__						=			Path(__lowercase		)
         # load model from hub
         else:
            # download model
            lowerCamelCase__						=			hf_hub_download(
                repo_id=__lowercase    ,						filename=__lowercase    ,						use_auth_token=__lowercase    ,						revision=__lowercase    ,						cache_dir=__lowercase    ,						force_download=__lowercase    ,						)
            lowerCamelCase__						=			Path(__lowercase		).parent
            lowerCamelCase__						=			Path(__lowercase		).name
            lowerCamelCase__						=			OnnxRuntimeModel.load_model(__lowercase    ,						provider=__lowercase    ,						sess_options=__lowercase		)
         return cls(model=__lowercase    ,						**__lowercase		)





      @classmethod
      def 					_lowerCamelCase  (  cls    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = True    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					Optional[Any]:
         lowerCamelCase__						=			None
         if len(str(__lowercase		).split("@"		)		) == 2:
            lowerCamelCase__					,       lowerCamelCase__						=			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"""




from __future__ import annotations

from typing import Any



def 	UpperCAmelCase__   (				A__   )      ->      None:




   """simple docstring"""
   create_state_space_tree(A__	,    []	,    0   )



def 	UpperCAmelCase__   (				A__	,    A__	,    A__   )      ->      None:




   """simple docstring"""

   if index == len(A__   ):
      print(A__   )
      return

   create_state_space_tree(A__	,    A__	,    index + 1   )
   current_subsequence.append(sequence[index]   )
   create_state_space_tree(A__	,    A__	,    index + 1   )
   current_subsequence.pop()


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_     :			list[Any]	  =			[3, 1, 2, 4]
     generate_all_subsequences(seq)

     seq.clear()
     seq.extend(['''A''', '''B''', '''C'''])
     generate_all_subsequences(seq)




