提交 99b47985 编写于 作者: C chenluyan

add unittest for PR#427

上级 a3b9d118
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
sys.path.append("../")
import unittest
import paddle.fluid as fluid
from paddleslim.prune import Pruner
from paddleslim.core import GraphWrapper
from paddleslim.prune import conv2d as conv2d_walker
from layers import conv_bn_layer
class TestPrune(unittest.TestCase):
def test_prune(self):
main_program = fluid.Program()
startup_program = fluid.Program()
# X X O X O
# conv1-->conv2-->sum1-->conv3-->conv4-->sum2-->align_out-->conv5
# | ^ | ^ |
# |____________| |____________________| ->gather_out-->conv6
# |
# ->lodset_out-->conv7
#
# X: prune output channels
# O: prune input channels
with fluid.program_guard(main_program, startup_program):
input = fluid.data(name="image", shape=[None, 3, 64, 64])
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
#test roi_align
rois = fluid.data(
name='rois', shape=[None, 4], dtype='float32')
align_out = fluid.layers.roi_align(input=sum2,
rois=rois,
pooled_height=7,
pooled_width=7,
spatial_scale=0.5,
sampling_ratio=-1)
conv5 = conv_bn_layer(align_out, 8, 3, "conv5")
#test gather
index = fluid.layers.data(name='index', shape=[-1, 1], dtype='int32')
gather_out = fluid.layers.gather(sum2, index)
conv6 = conv_bn_layer(gather_out, 8, 3, "conv6")
#test lod_reset
y = fluid.layers.data(name='y', shape=[6], lod_level=2)
lodset_out = fluid.layers.lod_reset(x=sum2, y=y)
conv7 = conv_bn_layer(lodset_out, 8, 3, "conv7")
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)
graph = GraphWrapper(main_program)
conv_op = graph.var("conv4_weights").outputs()[0]
walker = conv2d_walker(conv_op, [])
walker.prune(graph.var("conv4_weights"), pruned_axis=0, pruned_idx=[])
print(walker.pruned_params)
if __name__ == '__main__':
unittest.main()
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