UdeMDLCourse/dumolinTIMITtest.yaml at master · davidtob/UdeMDLCourse · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
!obj:pylearn2.train.Train {
    dataset: &train !obj:research.code.pylearn2.datasets.timit.TIMITOnTheFly {
        which_set: 'train',
        frame_length: 1,
        frames_per_example: &fpe 100,
        start: 0,
        noise: 0.001,
        audio_only: True
    },
    model: !obj:mlp_with_source.MLPWithSource {
        batch_size: 512,
        layers: [
            !obj:mlp_with_source.CompositeLayerWithSource {
                layer_name: 'c',
                layers: [
                    !obj:pylearn2.models.mlp.Linear {
                        layer_name: 'h1',
                        dim: 100,
                        irange: 0.05,
                    },
                    #!obj:pylearn2.models.mlp.Linear {
                    #    layer_name: 'h2',
                    #    dim: 62,
                    #    irange: 0.05,
                    #},
                ],
            },
            !obj:pylearn2.models.mlp.Linear {
                layer_name: 'o',
                dim: 1,
                irange: 0.05,
            },
        ],
        input_space: !obj:pylearn2.space.CompositeSpace {
            components: [
                !obj:pylearn2.space.VectorSpace {
                    dim: 100,
                },
                #!obj:pylearn2.space.VectorSpace {
                #    dim: 62,
                #},
            ],
        },
        input_source: ['features'],
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        learning_rate: .001,
        #monitoring_dataset: {
        #    'train': *train,
        #},
        cost: !obj:pylearn2.costs.mlp.Default {},
        termination_criterion: !obj:pylearn2.termination_criteria.EpochCounter {
            max_epochs: 10,
        },
        batches_per_iter: 1,
    },
}