Mercurial > ift6266
diff deep/stacked_dae/v_sylvain/nist_byclass_error.py @ 446:9fb893d039c6
Ajout de fonctionnalite pour calculer les erreurs de validation avec PNIST et P07
| author | SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca> |
|---|---|
| date | Tue, 04 May 2010 19:59:14 -0400 |
| parents | eb42bed0c13b |
| children |
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--- a/deep/stacked_dae/v_sylvain/nist_byclass_error.py Tue May 04 11:17:27 2010 -0400 +++ b/deep/stacked_dae/v_sylvain/nist_byclass_error.py Tue May 04 19:59:14 2010 -0400 @@ -57,6 +57,7 @@ examples_per_epoch = NIST_ALL_TRAIN_SIZE PATH = '' + NIST_BY_CLASS=0 @@ -75,64 +76,100 @@ if os.path.exists(PATH+'params_finetune_NIST.txt'): print ('\n finetune = NIST ') optimizer.reload_parameters(PATH+'params_finetune_NIST.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) if os.path.exists(PATH+'params_finetune_P07.txt'): print ('\n finetune = P07 ') optimizer.reload_parameters(PATH+'params_finetune_P07.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) if os.path.exists(PATH+'params_finetune_NIST_then_P07.txt'): print ('\n finetune = NIST then P07') optimizer.reload_parameters(PATH+'params_finetune_NIST_then_P07.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) if os.path.exists(PATH+'params_finetune_P07_then_NIST.txt'): print ('\n finetune = P07 then NIST') optimizer.reload_parameters(PATH+'params_finetune_P07_then_NIST.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) if os.path.exists(PATH+'params_finetune_PNIST07.txt'): print ('\n finetune = PNIST07') optimizer.reload_parameters(PATH+'params_finetune_PNIST07.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) if os.path.exists(PATH+'params_finetune_PNIST07_then_NIST.txt'): print ('\n finetune = PNIST07 then NIST') optimizer.reload_parameters(PATH+'params_finetune_PNIST07_then_NIST.txt') - print "NIST DIGITS" - optimizer.training_error(datasets.nist_digits(),part=2) - print "NIST LOWER CASE" - optimizer.training_error(datasets.nist_lower(),part=2) - print "NIST UPPER CASE" - optimizer.training_error(datasets.nist_upper(),part=2) + if NIST_BY_CLASS == 1: + print "NIST DIGITS" + optimizer.training_error(datasets.nist_digits(),part=2) + print "NIST LOWER CASE" + optimizer.training_error(datasets.nist_lower(),part=2) + print "NIST UPPER CASE" + optimizer.training_error(datasets.nist_upper(),part=2) + else: + print "P07 valid" + optimizer.training_error(datasets.nist_P07(),part=1) + print "PNIST valid" + optimizer.training_error(datasets.PNIST07(),part=1) channel.save()