code: def _fuse_bn_tensor(self, branch):
      if branch is None:
          return 0, 0
      kernel = branch.conv.weight
      running_mean = branch.bn._mean
      running_var = branch.bn._variance
      gamma = branch.bn.weight
      beta = branch.bn.bias
      eps = branch.bn._epsilon
      std = (running_var + eps).sqrt()
      t = (gamma / std).reshape((-1, 1, 1, 1))
      return kernel * t, beta - running_mean * gamma / std
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Constant
  from ppdet.modeling.ops import get_act_fn
  from ppdet.core.workspace import register, serializable
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 6 for calling the RepVggBlock obj's underlying member method code with example usage: obj._fuse_bn_tensor(branch) and returns: unknown,  unknown, int,  int