test_conv.py 文件源码

def test_broadcast_grad():
    # rng = numpy.random.RandomState(utt.fetch_seed())
    x1 = T.tensor4('x')
    # x1_data = rng.randn(1, 1, 300, 300)
    sigma = T.scalar('sigma')
    # sigma_data = 20
    window_radius = 3

    filter_1d = T.arange(-window_radius, window_radius + 1)
    filter_1d = filter_1d.astype(theano.config.floatX)
    filter_1d = T.exp(-0.5 * filter_1d**2 / sigma ** 2)
    filter_1d = filter_1d / filter_1d.sum()

    filter_W = filter_1d.dimshuffle(['x', 'x', 0, 'x'])

    y = theano.tensor.nnet.conv2d(x1, filter_W, border_mode='full',
                                  filter_shape=[1, 1, None, None])
    theano.grad(y.sum(), sigma)