class_docstr: Model for thread-safe inference.
  To do inference, you need to first initiate an InferenceModel instance, then call
  load|load_caffe|load_openvino to load a pre-trained model, and finally call predict.
  
  # Arguments
  supported_concurrent_num: Int. How many concurrent threads to invoke. Default is 1.
class_docstr_tok: ["Model","for","thread-safe","inference",".","To","do","inference",",","you","need","to","first","initiate","an","InferenceModel","instance",",","then","call","load|load_caffe|load_openvino","to","load","a","pre-trained","model",",","and","finally","call","predict",".","#","Arguments","supported_concurrent_num",":","Int",".","How","many","concurrent","threads","to","invoke",".","Default","is","1","."]
code: def __init__(
      self, supported_concurrent_num: int = 1, bigdl_type: str = "float"
  ) -> None:
      super(InferenceModel, self).__init__(
          None, bigdl_type, supported_concurrent_num
      )
  
imports: import warnings
  from bigdl.dllib.utils.common import JavaValue
  from bigdl.dllib.utils.file_utils import callZooFunc
  from bigdl.dllib.keras.engine.topology import KerasNet
  from bigdl.dllib.nn.layer import Layer
  from bigdl.dllib.utils.log4Error import invalidInputError
  from typing import Any, Union, Optional, List
  from typing import TYPE_CHECKING
label_desc: Use image node_id 1 to create a new InferenceModel object from inherited base classes: JavaValue with example: obj = InferenceModel(supported_concurrent_num, bigdl_type)