class_docstr: A helper class for handling relay functions from darknet model.
docstr: Parse the weights for batchnorm, which includes, scales, moving mean
  and moving variances.
docstr_tok: ["Parse","the","weights","for","batchnorm",",","which","includes",",","scales",",","moving","mean","and","moving","variances","."]
code: def _get_batchnorm_weights(self, layer, opname, size):
      """Parse the weights for batchnorm, which includes, scales, moving mean
      and moving variances."""
      scales = self._read_memory_buffer((size,), layer.scales)
      rolling_mean = self._read_memory_buffer(
          (size,), layer.rolling_mean
      )
      rolling_variance = self._read_memory_buffer(
          (size,), layer.rolling_variance
      )
  
      params = {}
      k = _get_params_name(opname, "moving_mean")
      params[k] = tvm.nd.array(rolling_mean)
      k = _get_params_name(opname, "moving_var")
      params[k] = tvm.nd.array(rolling_variance)
      k = _get_params_name(opname, "gamma")
      params[k] = tvm.nd.array(scales)
      return params
  
imports: from enum import Enum
  import numpy
  import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from .common import get_relay_op, new_var
label_desc: Use image node_id 7 for calling the GraphProto obj's underlying member method code with example usage: obj._get_batchnorm_weights(layer, opname, size) and returns: params