def METHOD_NAME(keras_layer, input_names, input_shapes, data_reader):
    assert 'QConv' in keras_layer['class_name']
    if '1D' in keras_layer['class_name']:
        layer, output_shape = parse_conv1d_layer(keras_layer, input_names, input_shapes, data_reader)
    elif '2D' in keras_layer['class_name']:
        layer, output_shape = parse_conv2d_layer(keras_layer, input_names, input_shapes, data_reader)
    layer['weight_quantizer'] = get_quantizer_from_config(keras_layer, 'kernel')
    if keras_layer['config']['bias_quantizer'] is not None:
        layer['bias_quantizer'] = get_quantizer_from_config(keras_layer, 'bias')
    else:
        layer['bias_quantizer'] = None
    return layer, output_shape