def convert_constant(params, w_name, scope_name, inputs, layers, weights, names):
print('<STR_LIT>')<EOL>params_list = params['<STR_LIT:value>'].numpy()<EOL>def target_layer(x, value=params_list):<EOL><INDENT>return tf.constant(value.tolist(), shape=value.shape)<EOL><DEDENT>lambda_layer = keras.layers.Lambda(target_layer)<EOL>layers[scope_name + '<STR_LIT>'] = params_list  <EOL>layers[scope_name] = lambda_layer(layers[list(layers.keys())[<NUM_LIT:0>]])<EOL>
Convert constant 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