code: def get_equivalent_kernel_bias(self):
      st1_kernel3x3, st1_bias3x3 = self._fuse_bn_tensor(self.depth_conv)
      st1_kernel1x1, st1_bias1x1 = self._fuse_bn_tensor(self.rbr_1x1)
      st1_kernelid, st1_biasid = self._fuse_bn_tensor(
          self.rbr_identity_st1, kernel_size=self.kernel_size
      )
  
      st2_kernel1x1, st2_bias1x1 = self._fuse_bn_tensor(self.point_conv)
      st2_kernelid, st2_biasid = self._fuse_bn_tensor(
          self.rbr_identity_st2, kernel_size=1
      )
  
      conv1_kernel = (
          st1_kernel3x3
          + self._pad_1x1_to_3x3_tensor(st1_kernel1x1)
          + st1_kernelid
      )
  
      conv1_bias = st1_bias3x3 + st1_bias1x1 + st1_biasid
  
      conv2_kernel = st2_kernel1x1 + st2_kernelid
      conv2_bias = st2_bias1x1 + st2_biasid
  
      return conv1_kernel, conv1_bias, conv2_kernel, conv2_bias
  
file_path: PaddleDetection/ppdet/modeling/backbones/mobileone.py
imports: import paddle
  import paddle.nn
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Normal, Constant
  from ppdet.modeling.ops import get_act_fn
  from ppdet.modeling.layers import ConvNormLayer
label_desc: Use image node_id 4 for calling the MobileOneBlock obj's underlying member method code with example usage: obj.get_equivalent_kernel_bias() and returns: conv1_kernel,  conv1_bias,  conv2_kernel,  conv2_bias