from paddle.trainer_config_helpers import * settings(learning_rate=1e-3, batch_size=1000) img = data_layer(name='image', size=256 * 256) # the parse_conv in config_parse.py is not strictly accurate when filter_size # is not square. So here set square filter_size. img_conv = img_conv_layer( input=img, num_channels=1, num_filters=64, filter_size=(32, 32), padding=(1, 1), dilation=(1, 1), stride=(1, 1), act=LinearActivation()) img_bn = batch_norm_layer(input=img_conv, act=ReluActivation()) img_norm = img_cmrnorm_layer(input=img_bn, size=32) img_pool = img_pool_layer(input=img_conv, pool_size=32, pool_type=MaxPooling()) outputs(img_pool, img_norm)