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96 lines
3.3 KiB
96 lines
3.3 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 op_test import OpTest
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import unittest
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import numpy as np
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import six
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class CrossEntropy2OpTestBase(OpTest):
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def initParameters(self):
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return [32, 64], 'float32', -100, False
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def calc_output(self, logits, label, ignore_index):
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ret = np.zeros(shape=label.shape, dtype=logits.dtype)
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match_x = np.zeros(shape=label.shape, dtype=logits.dtype)
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for idx in six.moves.range(label.shape[0]):
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if label[idx] == ignore_index:
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continue
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match_x[idx] = logits[idx][label[idx]]
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ret[idx] = -np.log(match_x[idx])
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return ret, match_x
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def setUp(self):
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self.shape, self.dtype, self.ignore_index, self.drop_last_dim = self.initParameters(
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)
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self.op_type = 'cross_entropy2'
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feature_size = int(self.shape[-1])
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batch_size = int(np.prod(self.shape) / feature_size)
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logits = (np.random.random(size=self.shape) + 1).astype(self.dtype)
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label_shape = self.shape[0:-1] if self.drop_last_dim else self.shape[
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0:-1] + [1]
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label = np.random.random_integers(
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low=0, high=feature_size - 1, size=label_shape).astype('int64')
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outputs, match_x = self.calc_output(
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np.reshape(logits, [batch_size, feature_size]),
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np.reshape(label, [batch_size, 1]), self.ignore_index)
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self.inputs = {'X': logits, 'Label': label}
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out_shape = label_shape
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self.outputs = {
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'Y': np.reshape(outputs, out_shape),
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'MatchX': np.reshape(match_x, self.shape[:-1] + [1]),
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'XShape': np.zeros(
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shape=logits.shape, dtype=logits.dtype)
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}
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self.attrs = {'ignore_index': self.ignore_index}
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def test_check_output(self):
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self.check_output(no_check_set=['XShape'])
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def test_check_grad(self):
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self.check_grad(
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inputs_to_check=['X'],
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output_names=['Y'],
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no_grad_set=['XShape', 'MatchX', 'Label'])
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class CrossEntropy2OpTest2(CrossEntropy2OpTestBase):
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def initParameters(self):
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return [32, 64], 'float64', 3, False
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class CrossEntropy2OpTest2RemoveLastDim(CrossEntropy2OpTestBase):
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def initParameters(self):
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return [32, 64], 'float64', 3, True
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class CrossEntropy2OpTest3(CrossEntropy2OpTestBase):
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def initParameters(self):
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return [4, 8, 16, 32], 'float32', -100, False
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class CrossEntropy2OpTest3RemoveLastDim(CrossEntropy2OpTestBase):
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def initParameters(self):
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return [4, 8, 16, 32], 'float32', -100, True
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class CrossEntropy2OpTest4(CrossEntropy2OpTestBase):
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def initParameters(self):
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return [4, 8, 16, 32], 'float32', 3, False
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if __name__ == '__main__':
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unittest.main()
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