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=1, bigdl_type="float"):
      super(InferenceModel, self).__init__(
          None, bigdl_type, supported_concurrent_num
      )
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/inference/inference_model.py
imports: from bigdl.util.common import JavaValue
  from zoo.common.utils import callZooFunc
  from bigdl.nn.layer import Layer
  from zoo.pipeline.api.keras.engine import KerasNet
  import warnings
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)