@staticmethod
    def get_batch(x, y=None, batch_size=128, batch_ind=0, inds=None):
        if inds is None:
            inds = np.arange(x.shape[0])
        batch_x = x[inds[batch_ind*batch_size:(batch_ind+1)*batch_size],...]
        batch_y = None
        if y is not None:
            batch_y = y[inds[batch_ind*batch_size:(batch_ind+1)*batch_size],...]

        return batch_x, batch_y
Calculate the gradient of the cost function with respect to all learnable parameters of this
dataset/ETHPy150Open bbabenko/simple_convnet/simple_convnet/convnet.py/NNet.get_batch