class_docstr: ONNXRuntime will use numpy as data type.
  ONNXRuntime quantization in torch will use torchmetrics
class_docstr_tok: ["ONNXRuntime","will","use","numpy","as","data","type",".","ONNXRuntime","quantization","in","torch","will","use","torchmetrics"]
code: def to_scalar(self, tensor):
      return tensor.item()
  
imports: from ..metric import ONNXRuntimeINCMetic
  import torch
label_desc: Use image node_id 2 for calling the PytorchONNXRuntimeINCMetic obj's underlying member method code with example usage: obj.to_scalar(tensor) and returns: tensor