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comparison deep/stacked_dae/nist_sda.py @ 186:d364a130b221

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Ajout du code de base pour scalar_series. Modifications à stacked_dae: réglé un problème avec les input_divider (empêchait une optimisation), et ajouté utilisation des séries. Si j'avais pas déjà commité, aussi, j'ai enlevé l'histoire de réutilisation du pretraining: c'était compliqué (error prone) et ça créait des jobs beaucoup trop longues.
author fsavard
date Mon, 01 Mar 2010 11:45:25 -0500
parents b9ea8e2d071a
children 3632e6258642 c69c1d832a53
comparison
equal deleted inserted replaced
185:b9ea8e2d071a 186:d364a130b221
30 from scalar_series import * 30 from scalar_series import *
31 SERIES_AVAILABLE = True 31 SERIES_AVAILABLE = True
32 except ImportError: 32 except ImportError:
33 print "Could not import Series" 33 print "Could not import Series"
34 34
35 TEST_CONFIG = True 35 TEST_CONFIG = False
36 36
37 NIST_ALL_LOCATION = '/data/lisa/data/nist/by_class/all' 37 NIST_ALL_LOCATION = '/data/lisa/data/nist/by_class/all'
38 38
39 JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_db/fsavard_sda2' 39 JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_db/fsavard_sda2'
40 40
44 if TEST_CONFIG: 44 if TEST_CONFIG:
45 REDUCE_TRAIN_TO = 1000 45 REDUCE_TRAIN_TO = 1000
46 MAX_FINETUNING_EPOCHS = 2 46 MAX_FINETUNING_EPOCHS = 2
47 REDUCE_EVERY = 10 47 REDUCE_EVERY = 10
48 48
49 EXPERIMENT_PATH = "ift6266.scripts.stacked_dae.nist_sda.jobman_entrypoint" 49 EXPERIMENT_PATH = "ift6266.deep.stacked_dae.nist_sda.jobman_entrypoint"
50 50
51 JOB_VALS = {'pretraining_lr': [0.1, 0.01],#, 0.001],#, 0.0001], 51 JOB_VALS = {'pretraining_lr': [0.1, 0.01],#, 0.001],#, 0.0001],
52 'pretraining_epochs_per_layer': [10,20], 52 'pretraining_epochs_per_layer': [10,20],
53 'hidden_layers_sizes': [300,800], 53 'hidden_layers_sizes': [300,800],
54 'corruption_levels': [0.1,0.2,0.3], 54 'corruption_levels': [0.1,0.2,0.3],