test_prune.py

import sys
sys.path.append("../")
import unittest
import paddle.fluid as fluid
from paddleslim.prune import Pruner
from layers import conv_bn_layer


class TestPrune(unittest.TestCase):
    def test_prune(self):
        main_program = fluid.Program()
        startup_program = fluid.Program()
        with fluid.program_guard(main_program, startup_program):
            input = fluid.data(name="image", shape=[None, 3, 16, 16])
            conv1 = conv_bn_layer(input, 8, 3, "conv1")
            conv2 = conv_bn_layer(conv1, 8, 3, "conv2")
            sum1 = conv1 + conv2
            conv3 = conv_bn_layer(sum1, 8, 3, "conv3")
            conv4 = conv_bn_layer(conv3, 8, 3, "conv4")
            sum2 = conv4 + sum1
            conv5 = conv_bn_layer(sum2, 8, 3, "conv5")
            conv6 = conv_bn_layer(conv5, 8, 3, "conv6")

        shapes = {}
        for param in main_program.global_block().all_parameters():
            shapes[param.name] = param.shape

        place = fluid.CPUPlace()
        exe = fluid.Executor(place)
        scope = fluid.Scope()
        exe.run(startup_program, scope=scope)
        pruner = Pruner()
        main_program = pruner.prune(
            main_program,
            scope,
            params=["conv4_weights"],
            ratios=[0.5],
            place=place,
            lazy=False,
            only_graph=False,
            param_backup=None,
            param_shape_backup=None)

        shapes = {
            "conv5_weights": (8L, 4L, 3L, 3L),
            "conv1_weights": (4L, 3L, 3L, 3L),
            "conv6_weights": (8L, 8L, 3L, 3L),
            "conv3_weights": (8L, 4L, 3L, 3L),
            "conv2_weights": (4L, 4L, 3L, 3L),
            "conv4_weights": (4L, 8L, 3L, 3L)
        }

        for param in main_program.global_block().all_parameters():
            if "weights" in param.name:
                self.assertTrue(param.shape == shapes[param.name])


if __name__ == '__main__':
    unittest.main()