test_average_pooling_2d.py 文件源码

def check_forward(self, x_data, use_cudnn=True):
        x = chainer.Variable(x_data)
        y = functions.average_pooling_2d(x, 3, stride=2,
                                         pad=1, use_cudnn=use_cudnn)
        self.assertEqual(y.data.dtype, self.dtype)
        y_data = cuda.to_cpu(y.data)

        self.assertEqual(self.gy.shape, y_data.shape)
        for k in six.moves.range(2):
            for c in six.moves.range(3):
                x = self.x[k, c]
                expect = numpy.array([
                    [x[0:2, 0:2].sum(), x[0:2, 1:3].sum()],
                    [x[1:4, 0:2].sum(), x[1:4, 1:3].sum()]]) / 9
                gradient_check.assert_allclose(
                    expect, y_data[k, c], **self.check_forward_options)