

def make_node(self, images):
    '\n        .. todo::\n\n            WRITEME\n        '
    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()
    seed = self.seed_state
    seed = as_cuda_ndarray_variable(channels_broadcastable)
    return Apply(self, [images, seed], [targets])

dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/sandbox/cuda_convnet/stochastic_pool.py StochasticMaxPool.make_node/VarMisuse@97/172 `seed`->`channels_broadcastable`