import unittest import paddle.v2.fluid as fluid import paddle.v2.fluid.nets as nets from paddle.v2.fluid.framework import Program def conv_block(input, num_filter, groups, dropouts): return nets.img_conv_group( input=input, pool_size=2, pool_stride=2, conv_num_filter=[num_filter] * groups, conv_filter_size=3, conv_act='relu', conv_with_batchnorm=True, conv_batchnorm_drop_rate=dropouts, pool_type='max') class TestLayer(unittest.TestCase): def test_batch_norm_layer(self): main_program = Program() startup_program = Program() with fluid.program_guard(main_program, startup_program): images = fluid.layers.data( name='pixel', shape=[3, 48, 48], dtype='float32') hidden1 = fluid.layers.batch_norm(input=images) hidden2 = fluid.layers.fc(input=hidden1, size=128, act='relu') fluid.layers.batch_norm(input=hidden2) print str(main_program) def test_dropout_layer(self): main_program = Program() startup_program = Program() with fluid.program_guard(main_program, startup_program): images = fluid.layers.data( name='pixel', shape=[3, 48, 48], dtype='float32') fluid.layers.dropout(x=images, dropout_prob=0.5) print str(main_program) def test_img_conv_group(self): main_program = Program() startup_program = Program() with fluid.program_guard(main_program, startup_program): images = fluid.layers.data( name='pixel', shape=[3, 48, 48], dtype='float32') conv1 = conv_block(images, 64, 2, [0.3, 0]) conv_block(conv1, 256, 3, [0.4, 0.4, 0]) print str(main_program) def test_elementwise_add_with_act(self): main_program = Program() startup_program = Program() with fluid.program_guard(main_program, startup_program): image1 = fluid.layers.data( name='pixel1', shape=[3, 48, 48], dtype='float32') image2 = fluid.layers.data( name='pixel2', shape=[3, 48, 48], dtype='float32') fluid.layers.elementwise_add(x=image1, y=image2, act='relu') print(main_program) if __name__ == '__main__': unittest.main()