






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 		_A						:

  def __init__(    self						:	List[Any]   ,				lowerCamelCase__						:	Any=None   ,				**lowerCamelCase__						:	Any			):
     """simple docstring"""

     logger.info("""`diffusers.OnnxRuntimeModel` is experimental and might change in the future."""			)
     __UpperCamelCase	:			List[str]					=					model
     __UpperCamelCase	:			str					=					kwargs.get("""model_save_dir"""   ,				lowerCamelCase__			)
     __UpperCamelCase	:			List[str]					=					kwargs.get("""latest_model_name"""   ,				lowerCamelCase__			)

  def __call__(    self						:	Dict   ,				**lowerCamelCase__						:	Optional[Any]			):
     """simple docstring"""

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

  @staticmethod
  def    a					(    lowerCamelCase__						:	Union[str, Path]   ,				lowerCamelCase__						:	Optional[int]=None   ,				lowerCamelCase__						:	Dict=None			):
     """simple docstring"""

     if provider is None:
        logger.info("""No onnxruntime provider specified, using CPUExecutionProvider"""			)
        __UpperCamelCase	:			List[Any]					=					"""CPUExecutionProvider"""

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

  def    a					(    self						:	Union[str, Any]   ,				lowerCamelCase__						:	Union[str, Path]   ,				lowerCamelCase__						:	Optional[str] = None   ,				**lowerCamelCase__						:	Dict			):
     """simple docstring"""

     __UpperCamelCase	:			Any					=					file_name if file_name is not None else ONNX_WEIGHTS_NAME

     __UpperCamelCase	:			Any					=					self.model_save_dir.joinpath(self.latest_model_name			)
     __UpperCamelCase	:			Optional[Any]					=					Path(lowerCamelCase__			).joinpath(lowerCamelCase__			)
     try:
        shutil.copyfile(lowerCamelCase__   ,				lowerCamelCase__			)
     except shutil.SameFileError:
        pass

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

  def    a					(    self						:	List[Any]   ,				lowerCamelCase__						:	Union[str, os.PathLike]   ,				**lowerCamelCase__						:	Optional[Any]   ,				):
     """simple docstring"""

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

     os.makedirs(lowerCamelCase__   ,				exist_ok=lowerCamelCase__			)

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

  @classmethod
  def    a					(    cls						:	Tuple   ,				lowerCamelCase__						:	Union[str, Path]   ,				lowerCamelCase__						:	Optional[Union[bool, str, None]] = None   ,				lowerCamelCase__						:	Optional[Union[str, None]] = None   ,				lowerCamelCase__						:	bool = False   ,				lowerCamelCase__						:	Optional[str] = None   ,				lowerCamelCase__						:	Optional[str] = None   ,				lowerCamelCase__						:	Optional[str] = None   ,				lowerCamelCase__						:	Optional["ort.SessionOptions"] = None   ,				**lowerCamelCase__						:	List[str]   ,				):
     """simple docstring"""

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

  @classmethod
  def    a					(    cls						:	Dict   ,				lowerCamelCase__						:	Union[str, Path]   ,				lowerCamelCase__						:	bool = True   ,				lowerCamelCase__						:	Optional[str] = None   ,				lowerCamelCase__						:	Optional[str] = None   ,				**lowerCamelCase__						:	Tuple   ,				):
     """simple docstring"""

     __UpperCamelCase	:			Optional[int]					=					None
     if len(str(lowerCamelCase__			).split("""@"""			)			) == 2:
        __UpperCamelCase	,     __UpperCamelCase	:			Dict					=					model_id.split("""@"""			)

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











import os

import pytest

from transformers.dynamic_module_utils import get_imports


UpperCamelCase    							=      '\nimport os\n'

UpperCamelCase    							=      '\ndef foo():\n    import os\n    return False\n'

UpperCamelCase    							=      '\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n'

UpperCamelCase    							=      [
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]


@pytest.mark.parametrize("""case"""					,							__lowerCAmelCase							)
def 				__lowerCamelCase     (							__lowerCAmelCase							:					List[Any]					,							__lowerCAmelCase							:					Optional[Any]							)     ->  str:
   __UpperCamelCase	:			str					=					os.path.join(__lowerCAmelCase					,							"""test_file.py"""							)
   with open(__lowerCAmelCase					,							"""w"""							) as _tmp_file:
      _tmp_file.write(__lowerCAmelCase							)

   __UpperCamelCase	:			Optional[int]					=					get_imports(__lowerCAmelCase							)
   assert parsed_imports == ["os"]



