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comparison deep/stacked_dae/v_sylvain/nist_sda.py @ 234:c452e3a0a3b1

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Changement de la base de donnees qui sera utilisee
author SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
date Sun, 14 Mar 2010 15:17:04 -0400
parents 8a94a5c808cd
children ecb69e17950b
comparison
equal deleted inserted replaced
233:02ed13244133 234:c452e3a0a3b1
35 # GLOBALS 35 # GLOBALS
36 36
37 TEST_CONFIG = False 37 TEST_CONFIG = False
38 38
39 #NIST_ALL_LOCATION = '/data/lisa/data/nist/by_class/all' 39 #NIST_ALL_LOCATION = '/data/lisa/data/nist/by_class/all'
40 JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_sandbox_db/fsavard_sda_v2' 40 JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_sandbox_db/sylvainpl_sda_vsylvain'
41 EXPERIMENT_PATH = "ift6266.deep.stacked_dae.v2.nist_sda.jobman_entrypoint" 41 EXPERIMENT_PATH = "ift6266.deep.stacked_dae.v_sylvain.nist_sda.jobman_entrypoint"
42 42
43 REDUCE_TRAIN_TO = None 43 REDUCE_TRAIN_TO = None
44 MAX_FINETUNING_EPOCHS = 1000 44 MAX_FINETUNING_EPOCHS = 1000
45 # number of minibatches before taking means for valid error etc. 45 # number of minibatches before taking means for valid error etc.
46 REDUCE_EVERY = 100 46 REDUCE_EVERY = 100
52 52
53 # Possible values the hyperparameters can take. These are then 53 # Possible values the hyperparameters can take. These are then
54 # combined with produit_cartesien_jobs so we get a list of all 54 # combined with produit_cartesien_jobs so we get a list of all
55 # possible combinations, each one resulting in a job inserted 55 # possible combinations, each one resulting in a job inserted
56 # in the jobman DB. 56 # in the jobman DB.
57 JOB_VALS = {'pretraining_lr': [0.1, 0.01],#, 0.001],#, 0.0001], 57 JOB_VALS = {'pretraining_lr': [0.1],#, 0.01],#, 0.001],#, 0.0001],
58 'pretraining_epochs_per_layer': [10,20], 58 'pretraining_epochs_per_layer': [10],
59 'hidden_layers_sizes': [300,800], 59 'hidden_layers_sizes': [500],
60 'corruption_levels': [0.1,0.2,0.3], 60 'corruption_levels': [0.1],
61 'minibatch_size': [20], 61 'minibatch_size': [20],
62 'max_finetuning_epochs':[MAX_FINETUNING_EPOCHS], 62 'max_finetuning_epochs':[MAX_FINETUNING_EPOCHS],
63 'finetuning_lr':[0.1, 0.01], #0.001 was very bad, so we leave it out 63 'finetuning_lr':[0.1], #0.001 was very bad, so we leave it out
64 'num_hidden_layers':[2,3]} 64 'num_hidden_layers':[1,1]}
65 65
66 # Just useful for tests... minimal number of epochs 66 # Just useful for tests... minimal number of epochs
67 DEFAULT_HP_NIST = DD({'finetuning_lr':0.1, 67 DEFAULT_HP_NIST = DD({'finetuning_lr':0.1,
68 'pretraining_lr':0.1, 68 'pretraining_lr':0.1,
69 'pretraining_epochs_per_layer':2, 69 'pretraining_epochs_per_layer':2,
70 'max_finetuning_epochs':2, 70 'max_finetuning_epochs':2,
71 'hidden_layers_sizes':800, 71 'hidden_layers_sizes':500,
72 'corruption_levels':0.2, 72 'corruption_levels':0.2,
73 'minibatch_size':20, 73 'minibatch_size':20,
74 'reduce_train_to':10000, 74 #'reduce_train_to':10000,
75 'num_hidden_layers':1}) 75 'num_hidden_layers':1})
76 76
77 ''' 77 '''
78 Function called by jobman upon launching each job 78 Function called by jobman upon launching each job
79 Its path is the one given when inserting jobs: see EXPERIMENT_PATH 79 Its path is the one given when inserting jobs: see EXPERIMENT_PATH