def make_node(self, images):
        images = as_cuda_ndarray_variable(images)

        assert images.ndim == 4

        channels_broadcastable = images.type.broadcastable[0]
        batch_broadcastable = images.type.broadcastable[3]

        rows_broadcastable = False
        cols_broadcastable = False

        targets_broadcastable = (channels_broadcastable, rows_broadcastable,
                cols_broadcastable, batch_broadcastable)
        targets_type = CudaNdarrayType(broadcastable=targets_broadcastable)
        targets = targets_type()

        return Apply(self, [images], [targets])
Returns a single feedback thread by an anonymous user.
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/sandbox/cuda_convnet/stochastic_pool.py/WeightedMaxPool.make_node--crossover with--dataset/ETHPy150Open oppia/oppia/core/controllers/home_test.py/NotificationsDashboardHandlerTest._get_recent_notifications_mock_by_anonymous_user