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Paddle/python/paddle/v2/fluid/tests/test_image_classification_l...

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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,
main_program=None,
startup_program=None):
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',
main_program=main_program,
startup_program=startup_program)
class TestLayer(unittest.TestCase):
def test_batch_norm_layer(self):
main_program = Program()
startup_program = Program()
images = fluid.layers.data(
name='pixel',
shape=[3, 48, 48],
dtype='float32',
main_program=main_program)
hidden1 = fluid.layers.batch_norm(
input=images,
main_program=main_program,
startup_program=startup_program)
hidden2 = fluid.layers.fc(input=hidden1,
size=128,
act='relu',
main_program=main_program)
hidden3 = fluid.layers.batch_norm(
input=hidden2,
main_program=main_program,
startup_program=startup_program)
print str(main_program)
def test_dropout_layer(self):
main_program = Program()
startup_program = Program()
images = fluid.layers.data(
name='pixel',
shape=[3, 48, 48],
dtype='float32',
main_program=main_program)
fluid.layers.dropout(
x=images,
dropout_prob=0.5,
main_program=main_program,
startup_program=startup_program)
# print str(main_program)
def test_img_conv_group(self):
main_program = Program()
startup_program = Program()
images = fluid.layers.data(
name='pixel',
shape=[3, 48, 48],
dtype='float32',
main_program=main_program,
startup_program=startup_program)
conv1 = conv_block(images, 64, 2, [0.3, 0], main_program,
startup_program)
conv2 = conv_block(conv1, 256, 3, [0.4, 0.4, 0], main_program,
startup_program)
# print str(main_program)
def test_elementwise_add_with_act(self):
main_program = Program()
startup_program = Program()
image1 = fluid.layers.data(
name='pixel1',
shape=[3, 48, 48],
dtype='float32',
main_program=main_program,
startup_program=startup_program)
image2 = fluid.layers.data(
name='pixel2',
shape=[3, 48, 48],
dtype='float32',
main_program=main_program,
startup_program=startup_program)
out = fluid.layers.elementwise_add(
x=image1,
y=image2,
act='relu',
main_program=main_program,
startup_program=startup_program)
# print(main_program)
if __name__ == '__main__':
unittest.main()