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","."]
docstr: Load a pytorch model.
  
  :param model_path: the path of saved pytorch model
     
docstr_tok: ["Load","a","pytorch","model",".",":","param","model_path",":","the","path","of","saved","pytorch","model"]
code: def load_torch(self, model_path: str) -> None:
      """
      Load a pytorch model.
  
      :param model_path: the path of saved pytorch model
      """
      invalidInputError(
          isinstance(model_path, str), "model_path should be string"
      )
      import io
      import torch
      from bigdl.orca.torch import zoo_pickle_module
  
      model = torch.load(model_path, pickle_module=zoo_pickle_module)
      bys = io.BytesIO()
      torch.save(model, bys, pickle_module=zoo_pickle_module)
      callZooFunc(
          self.bigdl_type,
          "inferenceModelLoadPytorch",
          self.value,
          bys.getvalue(),
      )
  
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 9 for calling the InferenceModel obj's underlying member method code with example usage: obj.load_torch(model_path) without return types