def convert_reduce_sum(params, w_name, scope_name, inputs, layers, weights, names):
print('<STR_LIT>')<EOL>keepdims = params['<STR_LIT>'] > <NUM_LIT:0><EOL>axis = params['<STR_LIT>']<EOL>def target_layer(x, keepdims=keepdims, axis=axis):<EOL><INDENT>import keras.backend as K<EOL>return K.sum(x, keepdims=keepdims, axis=axis)<EOL><DEDENT>lambda_layer = keras.layers.Lambda(target_layer)<EOL>layers[scope_name] = lambda_layer(layers[inputs[<NUM_LIT:0>]])<EOL>
Convert reduce_sum layer.

Args:
    params: dictionary with layer parameters
    w_name: name prefix in state_dict
    scope_name: pytorch scope name
    inputs: pytorch node inputs
    layers: dictionary with keras tensors
    weights: pytorch state_dict
    names: use short names for keras layers