sgd_mnist.yaml

!obj:pylearn2.scripts.train.Train {
    dataset:  &train !obj:pylearn2.datasets.mnist.MNIST {
        which_set: "train",
        binarize: 1,
        one_hot: 1,
        start: 0,
        stop: 50000
    },
    model: !obj:galatea.sample_prop.basic.SimpleModel {
        nvis: 784,
        num_hid: 500,
        num_class: 10
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
               batch_size: 100,
               learning_rate: 1e-3,
               set_batch_size: 1,
               monitoring_dataset: *train, #{
                                #'train' : *train,
                                #'valid' : !obj:pylearn2.datasets.mnist.MNIST {
                                #        which_set: "train",
                                #        binarize: 1,
                                #        one_hot: 1,
                                #        start: 50000,
                                #        stop:  60000
                                #        }
               #},
               cost : !obj:galatea.sample_prop.basic.SamplingCost {
               },
        },
    save_path: "${PYLEARN2_TRAIN_FILE_FULL_STEM}.pkl",
    save_freq : 1
}