

def test_train_batch():
    m = 1
    dim = 2
    rng = np.random.RandomState([2014, 3, 17])
    X = rng.randn(m, dim)
    train = DenseDesignMatrix(X=X)
    rbm = RBM(nvis=dim, nhid=3)
    trainer = DefaultTrainingAlgorithm(batch_size=1, batches_per_iter=10)
    trainer.setup(rbm, train)
    trainer.train(X)

dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/tests/test_rbm.py test_train_batch/VarMisuse@93/110 `train`->`X`