






'''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


A:      List[Any]  				=				logging.get_logger(__name__)

A:      List[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 							__magic_name__     :







	"""simple docstring"""



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

							return ort.InferenceSession(_lowercase  ,      providers=[provider]  ,      sess_options=_lowercase       )
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None  ,      **_lowercase       )						->  Dict:
							lowercase_      :   Any        =			file_name if file_name is not None else ONNX_WEIGHTS_NAME

							lowercase_      :   Any        =			self.model_save_dir.joinpath(self.latest_model_name       )
							lowercase_      :   Dict        =			Path(_lowercase       ).joinpath(_lowercase       )
							try:
													shutil.copyfile(_lowercase  ,      _lowercase       )
							except shutil.SameFileError:
													pass

							# copy external weights (for models >2GB)
							lowercase_      :   Optional[Any]        =			self.model_save_dir.joinpath(_lowercase       )
							if src_path.exists():
													lowercase_      :   Optional[int]        =			Path(_lowercase       ).joinpath(_lowercase       )
													try:
																			shutil.copyfile(_lowercase  ,      _lowercase       )
													except shutil.SameFileError:
																			pass
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      **_lowercase  ,      )						->  List[str]:
							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  ,      _lowercase  ,      _lowercase = None  ,      _lowercase = None  ,      _lowercase = False  ,      _lowercase = None  ,      _lowercase = None  ,      _lowercase = None  ,      _lowercase = None  ,      **_lowercase  ,      )						->  Any:
							lowercase_      :   Dict        =			file_name if file_name is not None else ONNX_WEIGHTS_NAME
							# load model from local directory
							if os.path.isdir(_lowercase       ):
													lowercase_      :   Optional[int]        =			OnnxRuntimeModel.load_model(
													    os.path.join(_lowercase  ,      _lowercase       )  ,      provider=_lowercase  ,      sess_options=_lowercase       )
													lowercase_      :   str        =			Path(_lowercase       )
							# load model from hub
							else:
													# download model
													lowercase_      :   Optional[Any]        =			hf_hub_download(
													    repo_id=_lowercase  ,      filename=_lowercase  ,      use_auth_token=_lowercase  ,      revision=_lowercase  ,      cache_dir=_lowercase  ,      force_download=_lowercase  ,      )
													lowercase_      :   Union[str, Any]        =			Path(_lowercase       ).parent
													lowercase_      :   Optional[int]        =			Path(_lowercase       ).name
													lowercase_      :   List[Any]        =			OnnxRuntimeModel.load_model(_lowercase  ,      provider=_lowercase  ,      sess_options=_lowercase       )
							return cls(model=_lowercase  ,      **_lowercase       )







	@classmethod
	def        lowerCamelCase__		(							cls  ,      _lowercase  ,      _lowercase = True  ,      _lowercase = None  ,      _lowercase = None  ,      **_lowercase  ,      )						->  Optional[int]:
							lowercase_      :   List[str]        =			None
							if len(str(_lowercase       ).split('@'       )       ) == 2:
													lowercase_      :   int        =			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 ..utils import DummyObject, requires_backends






class 							__magic_name__     (	metaclass=UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      str        =  ['transformers', 'torch', 'note_seq']
	def __init__(							self  ,      *_lowercase  ,      **_lowercase       )						->  Dict:
							requires_backends(self  ,      ['transformers', 'torch', 'note_seq']       )
	@classmethod
	def        lowerCamelCase__		(							cls  ,      *_lowercase  ,      **_lowercase       )						->  List[str]:
							requires_backends(cls  ,      ['transformers', 'torch', 'note_seq']       )







	@classmethod
	def        lowerCamelCase__		(							cls  ,      *_lowercase  ,      **_lowercase       )						->  Dict:
							requires_backends(cls  ,      ['transformers', 'torch', 'note_seq']       )
