def dbn_template1(self,
dataset_name='skdata.larochelle_etal_2007.Rectangles',
sup_min_epochs=300,
sup_max_epochs=4000):
template = rSON2(
'preprocessing', one_of(
rSON2(
'kind', 'raw'),
rSON2(
'kind', 'zca',
'energy', uniform(0.5, 1.0))),
'dataset_name', dataset_name,
'sup_max_epochs', sup_max_epochs,
'sup_min_epochs', sup_min_epochs,
'iseed', one_of(5, 6, 7, 8),
'batchsize', one_of(20, 100),
'lr', lognormal(numpy.log(.01), 3),
'lr_anneal_start', geom(100, 10000),
'l2_penalty', one_of(0, lognormal(numpy.log(1.0e-6), 2)),
'next_layer', one_of(None,
rSON2(
'n_hid', geom(2**7, 2**12, round=16),
'W_init_dist', one_of('uniform', 'normal'),
'W_init_algo', one_of('old', 'Xavier'),
'W_init_algo_old_multiplier', lognormal(0.0, 1.0),
'cd_epochs', geom(1, 3000),
'cd_batchsize', 100,
'cd_sample_v0s', one_of(False, True),
'cd_lr', lognormal(numpy.log(.01), 2),
'cd_lr_anneal_start', geom(10, 10000),
'next_layer', None)))
return template
def dbn_template0(self,
dataset_name='skdata.larochelle_etal_2007.Rectangles',
sup_min_epochs=300,
sup_max_epochs=4000):
template = rSON2(
'preprocessing', one_of(
rSON2(
'kind', 'raw'),
rSON2(
'kind', 'zca',
'energy', uniform(0.5, 1.0))),
'dataset_name', dataset_name,
'sup_max_epochs', sup_max_epochs,
'sup_min_epochs', sup_min_epochs,
'iseed', one_of(5, 6, 7, 8),
'batchsize', one_of(20, 100),
'lr', lognormal(numpy.log(.01), 3),
'lr_anneal_start', geom(100, 10000),
'l2_penalty', one_of(0, lognormal(numpy.log(1.0e-6), 2)),
'next_layer', None)
return template