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comparison scripts/stacked_dae/mnist_sda.py @ 131:5c79a2557f2f

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Un peu de ménage dans code pour stacked DAE, splitté en fichiers dans un nouveau sous-répertoire.
author savardf
date Fri, 19 Feb 2010 08:43:10 -0500
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children 7d8366fb90bf
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130:38929c29b602 131:5c79a2557f2f
1 #!/usr/bin/python
2 # coding: utf-8
3
4 # Parameterize call to sgd_optimization for MNIST
5
6 import numpy
7 import theano
8 import time
9 import theano.tensor as T
10 from theano.tensor.shared_randomstreams import RandomStreams
11
12 from stacked_dae import sgd_optimization
13 import cPickle, gzip
14 from jobman import DD
15
16 MNIST_LOCATION = '/u/savardf/datasets/mnist.pkl.gz'
17
18 def sgd_optimization_mnist(learning_rate=0.1, pretraining_epochs = 2, \
19 pretrain_lr = 0.1, training_epochs = 5, \
20 dataset='mnist.pkl.gz'):
21 # Load the dataset
22 f = gzip.open(dataset,'rb')
23 # this gives us train, valid, test (each with .x, .y)
24 dataset = cPickle.load(f)
25 f.close()
26
27 n_ins = 28*28
28 n_outs = 10
29
30 hyperparameters = DD({'finetuning_lr':learning_rate,
31 'pretraining_lr':pretrain_lr,
32 'pretraining_epochs_per_layer':pretraining_epochs,
33 'max_finetuning_epochs':training_epochs,
34 'hidden_layers_sizes':[1000,1000,1000],
35 'corruption_levels':[0.2,0.2,0.2],
36 'minibatch_size':20})
37
38 sgd_optimization(dataset, hyperparameters, n_ins, n_outs)
39
40 if __name__ == '__main__':
41 sgd_optimization_mnist()
42