Mercurial > ift6266
diff deep/convolutional_dae/scdae.py @ 334:6143b23e2610
Name the important layers to be able to change them easily later.
| author | Arnaud Bergeron <abergeron@gmail.com> |
|---|---|
| date | Wed, 14 Apr 2010 16:06:43 -0400 |
| parents | 2937f2a421aa |
| children | 5ddb1878dfbc |
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--- a/deep/convolutional_dae/scdae.py Wed Apr 14 16:06:04 2010 -0400 +++ b/deep/convolutional_dae/scdae.py Wed Apr 14 16:06:43 2010 -0400 @@ -31,7 +31,7 @@ subsamplings, corruptions): layers.append(cdae(fsize, nfilt, old_nfilt, subs, corr, dtype)) old_nfilt = nfilt - return LayerStack(layers) + return LayerStack(layers, name='scdae') def mlp(layer_sizes, dtype): layers = [] @@ -40,7 +40,7 @@ layers.append(SimpleLayer(old_size, size, activation=nlins.tanh, dtype=dtype)) old_size = size - return LayerStack(layers) + return LayerStack(layers, name='mlp') def scdae_net(in_size, filter_sizes, num_filts, subsamplings, corruptions, layer_sizes, out_size, dtype): @@ -53,7 +53,8 @@ rl2 = ReshapeLayer((None, outs)) layer_sizes = [outs]+layer_sizes ls2 = mlp(layer_sizes, dtype) - lrl = SimpleLayer(layer_sizes[-1], out_size, activation=nlins.softmax) + lrl = SimpleLayer(layer_sizes[-1], out_size, activation=nlins.softmax, + name='output') return NNet([rl1, ls, rl2, ls2, lrl], error=errors.nll) def build_funcs(batch_size, img_size, filter_sizes, num_filters, subs,