code: def test_caffe_layers(self):
      temp = tempfile.mkdtemp()
      for testlayer in testlayers:
          name = testlayer.name
          definition = testlayer.definition
          shapes = testlayer.shapes
          prototxtfile = temp + name + ".prototxt"
          weightfile = temp + name + ".caffemodel"
          with open(prototxtfile, "w") as prototxt:
              prototxt.write(definition)
          caffe.set_mode_cpu()
          caffe.set_random_seed(100)
          net = caffe.Net(prototxtfile, caffe.TEST)
          inputs = []
          for shape in shapes:
              (inputName, size) = shape.items()[0]
              input = random.uniform(size=size)
              net.blobs[inputName].data[...] = input
              inputs.append(input)
          cafferesult = net.forward().get(name)
          net.save(weightfile)
          model = Model.load_caffe_model(
              prototxtfile, weightfile, bigdl_type="float"
          )
          model.set_seed(100)
          if len(inputs) == 1:
              inputs = inputs[0]
          bigdlResult = model.forward(inputs)
          print(cafferesult)
          print(bigdlResult)
          assert_allclose(cafferesult, bigdlResult, atol=1e-4, rtol=0)
  
file_path: BigDL/python/dllib/test/bigdl/caffe/test_caffe_layers.py
imports: from bigdl.dllib.nn.layer import *
  from bigdl.dllib.optim.optimizer import *
  from bigdl.dllib.utils.common import *
  import numpy
  import pytest
  import tempfile
  from numpy import random
  from numpy.testing import assert_allclose
  import caffe
  from caffe_layers import testlayers
label_desc: Use image node_id 1 for calling the TestCaffeLayers obj's underlying member method code with example usage: obj.test_caffe_layers() without return types