code: def convert_leakyrelu(net, node, module, builder):
      
  
      input_name, output_name = _get_input_output_name(net, node)
      name = node['name']
      inputs = node['inputs']
      args, _ = module.get_params()
      mx_non_linearity = _get_attrs(node)['act_type']
      if mx_non_linearity == 'elu':
          non_linearity = 'ELU'
          slope = _get_attrs(node)['slope'] if 'slope' in _get_attrs(node) else 0.25
          params = slope
      elif mx_non_linearity == 'leaky':
          non_linearity = 'LEAKYRELU'
          slope = _get_attrs(node)['slope'] if 'slope' in _get_attrs(node) else 0.25
          params = [slope]
      elif mx_non_linearity == 'prelu':
          non_linearity = 'PRELU'
          params = args[_get_node_name(net, inputs[1][0])].asnumpy()
      else:
          raise TypeError('Unknown activation type %s' % mx_non_linearity)
      builder.add_activation(name = name,
                             non_linearity = non_linearity,
                             input_name = input_name,
                             output_name = output_name,
                             params = params)
docs: Convert a leakyrelu layer from mxnet to coreml.
  
      Parameters
      ----------
      network: net
          A mxnet network object.
  
      layer: node
          Node to convert.
  
      module: module
          An module for MXNet
  
      builder: NeuralNetworkBuilder
          A neural network builder object.