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()
        seed = self.seed_state
        seed = as_cuda_ndarray_variable(seed)
        return Apply(self, [images, seed], [targets])
Return a blob containing the XML for a chart of *chart_type*
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/sandbox/cuda_convnet/stochastic_pool.py/StochasticMaxPool.make_node--crossover with--dataset/ETHPy150Open scanny/python-pptx/pptx/chart/data.py/ChartData.xml_bytes