





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__   : Dict					  = logging.get_logger(__name__)

UpperCamelCase__   : Optional[Any]					  = {
    """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   _UpperCamelCase  :







					'''simple docstring'''

					def __init__(						self    :  List[Any] ,					__lowercase    :  List[Any]=None ,					**__lowercase    :  int		):






						'''simple docstring'''







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





					def __call__(						self    :  Any ,					**__lowercase    :  Any		):






						'''simple docstring'''







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





					@staticmethod
					def        SCREAMING_SNAKE_CASE							(						__lowercase    :  Union[str, Path] ,					__lowercase    :  int=None ,					__lowercase    :  List[str]=None		):






						'''simple docstring'''







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

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





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






						'''simple docstring'''







						UpperCAmelCase_								=     file_name if file_name is not None else ONNX_WEIGHTS_NAME

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

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





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict ,					__lowercase    :  Union[str, os.PathLike] ,					**__lowercase    :  Union[str, 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        SCREAMING_SNAKE_CASE							(						cls    :  Union[str, 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    :  Dict ,					):






						'''simple docstring'''







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





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






						'''simple docstring'''







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

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









from torch import nn







class   _UpperCamelCase  (       nn.Module  ):







					'''simple docstring'''

					def __init__(						self    :  Dict ,					__lowercase    :  List[str] ,					__lowercase    :  Dict		):






						'''simple docstring'''







						super().__init__()
						UpperCAmelCase_								=     class_size
						UpperCAmelCase_								=     embed_size
						# self.mlp1 = nn.Linear(embed_size, embed_size)
						# self.mlp2 = (nn.Linear(embed_size, class_size))
						UpperCAmelCase_								=     nn.Linear(__lowercase ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Any ,					__lowercase    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.mlp(__lowercase		)
						return logits


