Fork自 PaddlePaddle / Paddle
import unittest import numpy as np from op_test import OpTest class TestLogLossOp(OpTest): def setUp(self): self.op_type = 'log_loss' samples_num = 32 predicted = np.random.uniform(0.1, 1.0, (samples_num, 1)).astype("float32") labels = np.random.randint(0, 2, (samples_num, 1)).astype("float32") epsilon = 1e-4 self.inputs = { 'Predicted': predicted, 'Labels': labels, } self.attrs = {'epsilon': epsilon} loss = -labels * np.log(predicted + epsilon) - ( 1 - labels) * np.log(1 - predicted + epsilon) self.outputs = {'Loss': loss} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['Predicted'], 'Loss', max_relative_error=0.03) if __name__ == '__main__': unittest.main()