code: def map_convolution(cls, node):
      parent, _ = node.get_only_parent()
      kwargs = cls.get_kernel_params(node, parent.output_shape)
      kwargs["kernel_shape"] = [
          node.kernel_parameters.k_h,
          node.kernel_parameters.k_w,
          parent.output_shape.channels,
          node.parameters.num_output,
      ]
      kwargs["use_bias"] = node.parameters.bias_term
      if node.parameters.dilation:
          dilation = node.parameters.dilation[0]
          if dilation != 1:
              kwargs["dilations"] = [1, dilation, dilation, 1]
      kwargs["group"] = node.parameters.group
      return Node.create("Conv", **kwargs)
  
imports: from __future__ import absolute_import
  from __future__ import division
  import numpy
  from mmdnn.conversion.caffe.errors import ConversionError
  from mmdnn.conversion.caffe.common_graph import Node
  from mmdnn.conversion.caffe.network import DEFAULT_PADDING
  from mmdnn.conversion.caffe.utils import get_lower_case
  from mmdnn.conversion.common.IR.graph_pb2 import TensorShape
label_desc: Use image node_id 5 for calling the NodeMapper obj's underlying member method code with example usage: obj.map_convolution(cls, node) and returns: Node