code: def _to_tensor(self):
      data = self.model_inputs[0].zvalue
      dim = sorted(tuple([int(i) for i in self.onnx_attr["axes"]]))
      for i in dim:
          data = autograd.expand_dims(data, axis=i)
      return data
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/onnx/mapper/unsqueeze.py
imports: from zoo.pipeline.api.onnx.mapper.operator_mapper import OperatorMapper
  import zoo.pipeline.api.keras.layers
  import numpy
  from zoo.pipeline.api.autograd import Parameter
  import bigdl.nn.layer
  import zoo.pipeline.api.autograd
label_desc: Use image node_id 3 for calling the UnsqueezeMapper obj's underlying member method code with example usage: obj._to_tensor() and returns: data