code: def _to_tensor(self):
      lens = []
      input = self.model_inputs[0].zvalue
      ends = self.onnx_attr["ends"]
      starts = self.onnx_attr["starts"]
      if "axes" in self.onnx_attr.keys():
          axes = self.onnx_attr["axes"]
      else:
          axes = range(len(starts))
      for j in range(len(starts)):
          lens.append(ends[j] - starts[j])
          # slice(, len=-1) equals to slice(, len=length)
          # y = x[:2,0:-1] means start is(0,0) and ends is(2,-1)
          # which is equivalent to slice(,len=-2) as "end=-1" is exclusive here.
          if lens[j] < 0:
              lens[j] -= 1
      for i in range(len(starts)):
          input = input.slice(
              dim=int(axes[i]),
              start_index=int(starts[i]),
              length=int(lens[i]),
          )
      return input
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/onnx/mapper/slice.py
imports: from zoo.pipeline.api.onnx.mapper.operator_mapper import OperatorMapper
  import zoo.pipeline.api.keras.layers
  import zoo.pipeline.api.autograd
  import bigdl.nn.layer
label_desc: Use image node_id 3 for calling the SliceMapper obj's underlying member method code with example usage: obj._to_tensor() and returns: input