parameters: (self, path_or_bytes, session_options=None, providers=None, provider_options=None)
docstring: :param path_or_bytes: filename or serialized ONNX or ORT format model in a byte string
          :param sess_options: session options
          :param providers: Optional sequence of providers in order of decreasing
              precedence. Values can either be provider names or tuples of
              (provider name, options dict). If not provided, then all available
              providers are used with the default precedence.
          :param provider_options: Optional sequence of options dicts corresponding
              to the providers listed in 'providers'.
  
          The model type will be inferred unless explicitly set in the SessionOptions.
          To explicitly set:
            so = onnxruntime.SessionOptions()
            so.add_session_config_entry('session.load_model_format', 'ONNX') or
            so.add_session_config_entry('session.load_model_format', 'ORT') or
  
          A file extension of '.ort' will be inferred as an ORT format model.
          All other filenames are assumed to be ONNX format models.
  
          'providers' can contain either names or names and options. When any options
          are given in 'providers', 'provider_options' should not be used.
  
          The list of providers is ordered by precedence. For example ['CUDAExecutionProvider', 'CPUExecutionProvider']
          means execute a node using CUDAExecutionProvider if capable, otherwise execute using CPUExecutionProvider.
docstring_summary: :param path_or_bytes: filename or serialized ONNX or ORT format model in a byte string
          :param sess_options: session options
          :param providers: Optional sequence of providers in order of decreasing
              precedence. Values can either be provider names or tuples of
              (provider name, options dict). If not provided, then all available
              providers are used with the default precedence.
          :param provider_options: Optional sequence of options dicts corresponding
              to the providers listed in 'providers'.
docstring_tokens: : param path_or_bytes : filename or serialized ONNX or ORT format model in a byte string : param sess_options : session options : param providers : Optional sequence of providers in order of decreasing precedence . Values can either be provider names or tuples of ( provider name options dict ) . If not provided then all available providers are used with the default precedence . : param provider_options : Optional sequence of options dicts corresponding to the providers listed in providers .
function: def __init__(self, path_or_bytes, session_options=None, providers=None, provider_options=None):
          """
          :param path_or_bytes: filename or serialized ONNX or ORT format model in a byte string
          :param sess_options: session options
          :param providers: Optional sequence of providers in order of decreasing
              precedence. Values can either be provider names or tuples of
              (provider name, options dict). If not provided, then all available
              providers are used with the default precedence.
          :param provider_options: Optional sequence of options dicts corresponding
              to the providers listed in 'providers'.
  
          The model type will be inferred unless explicitly set in the SessionOptions.
          To explicitly set:
            so = onnxruntime.SessionOptions()
            so.add_session_config_entry('session.load_model_format', 'ONNX') or
            so.add_session_config_entry('session.load_model_format', 'ORT') or
  
          A file extension of '.ort' will be inferred as an ORT format model.
          All other filenames are assumed to be ONNX format models.
  
          'providers' can contain either names or names and options. When any options
          are given in 'providers', 'provider_options' should not be used.
  
          The list of providers is ordered by precedence. For example ['CUDAExecutionProvider', 'CPUExecutionProvider']
          means execute a node using CUDAExecutionProvider if capable, otherwise execute using CPUExecutionProvider.
          """
  
          self._inference_session = None
  
          self.create_inference_agent(path_or_bytes, session_options, providers, provider_options)
function_tokens: def __init__ ( self , path_or_bytes , session_options = None , providers = None , provider_options = None ) : self . _inference_session = None self . create_inference_agent ( path_or_bytes , session_options , providers , provider_options )