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# Copyright (c) 2018 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 unittest
import numpy as np
from op_test import OpTest
from test_pool2d_op import max_pool2D_forward_naive
from test_pool2d_op import avg_pool2D_forward_naive
class TestSppOp(OpTest):
def setUp(self):
self.op_type = "spp"
self.init_test_case()
input = np.random.random(self.shape).astype("float32")
nsize, csize, hsize, wsize = input.shape
out_level_flatten = []
for i in xrange(self.pyramid_height):
bins = np.power(2, i)
kernel_size = [0, 0]
padding = [0, 0]
kernel_size[0] = np.ceil(hsize /
bins.astype("double")).astype("int32")
padding[0] = (
(kernel_size[0] * bins - hsize + 1) / 2).astype("int32")
kernel_size[1] = np.ceil(wsize /
bins.astype("double")).astype("int32")
padding[1] = (
(kernel_size[1] * bins - wsize + 1) / 2).astype("int32")
out_level = self.pool2D_forward_naive(input, kernel_size,
kernel_size, padding)
out_level_flatten.append(
out_level.reshape(nsize, bins * bins * csize))
if i == 0:
output = out_level_flatten[i]
else:
output = np.concatenate((output, out_level_flatten[i]), 1)
# output = np.concatenate(out_level_flatten.tolist(), 0);
self.inputs = {'X': input.astype('float32'), }
self.attrs = {
'pyramid_height': self.pyramid_height,
'pooling_type': self.pool_type
}
self.outputs = {'Out': output.astype('float32')}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
if self.pool_type != "avg":
self.check_grad(['X'], 'Out', max_relative_error=0.05)
def init_test_case(self):
self.shape = [3, 2, 4, 4]
self.pyramid_height = 3
self.pool2D_forward_naive = max_pool2D_forward_naive
self.pool_type = "max"
class TestCase2(TestSppOp):
def init_test_case(self):
self.shape = [3, 2, 4, 4]
self.pyramid_height = 3
self.pool2D_forward_naive = avg_pool2D_forward_naive
self.pool_type = "avg"
if __name__ == '__main__':
unittest.main()
