sgd_01_A.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.SampledClassModel {
        nvis: 784,
        num_hid: 500,
        num_class: 10
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
               batch_size: 100,
               set_batch_size: 1,
               learning_rate: 1e-2,
               init_momentum: .5,
               monitoring_dataset:
                                {
                                '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.ZeroOneLoss {
                        weight_decay_1: .000001,
                        weight_decay_2: .000001
               },
        },
    callbacks: [ !obj:pylearn2.training_algorithms.sgd.MomentumAdjustor {
        start: 0,
        saturate: 200,
        final_momentum: .99
    },
    !obj:pylearn2.training_algorithms.sgd.OneOverEpoch {
        start: 100,
        half_life: 5
    }
    ],
    save_path: "${PYLEARN2_TRAIN_FILE_FULL_STEM}.pkl",
    save_freq : 1
}