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96 lines
2.9 KiB
96 lines
2.9 KiB
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid.core as core
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class TestCenterLossOp(OpTest):
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def setUp(self):
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self.op_type = "center_loss"
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self.dtype = np.float32
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self.init_dtype_type()
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batch_size = 6
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feet_dim = 10
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cluster_num = 8
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self.attrs = {}
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self.attrs['cluster_num'] = cluster_num
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self.attrs['lambda'] = 0.1
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self.config()
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self.attrs['need_update'] = self.need_update
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labels = np.random.randint(cluster_num, size=batch_size, dtype='int64')
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feat = np.random.random((batch_size, feet_dim)).astype(np.float32)
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centers = np.random.random((cluster_num, feet_dim)).astype(np.float32)
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var_sum = np.zeros((cluster_num, feet_dim), dtype=np.float32)
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centers_select = centers[labels]
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output = feat - centers_select
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diff_square = np.square(output).reshape(batch_size, feet_dim)
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loss = 0.5 * np.sum(diff_square, axis=1).reshape(batch_size, 1)
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cout = []
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for i in range(cluster_num):
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cout.append(0)
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for i in range(batch_size):
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cout[labels[i]] += 1
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var_sum[labels[i]] += output[i]
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for i in range(cluster_num):
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var_sum[i] /= (1 + cout[i])
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var_sum *= 0.1
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result = centers + var_sum
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rate = np.array([0.1]).astype(np.float32)
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self.inputs = {
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'X': feat,
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'Label': labels,
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'Centers': centers,
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'CenterUpdateRate': rate
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}
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if self.need_update == True:
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self.outputs = {
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'SampleCenterDiff': output,
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'Loss': loss,
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'CentersOut': result
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}
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else:
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self.outputs = {
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'SampleCenterDiff': output,
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'Loss': loss,
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'CentersOut': centers
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}
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def config(self):
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self.need_update = True
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def init_dtype_type(self):
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pass
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['X'], 'Loss')
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class TestCenterLossOpNoUpdate(TestCenterLossOp):
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def config(self):
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self.need_update = False
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if __name__ == "__main__":
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unittest.main()
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