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comparison deep/stacked_dae/v_sylvain/nist_sda.py @ 319:7a12d2c3d06b

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finetune NIST+P07 change pour P07+NIST, les experiences n'ont pas ete concluentes
author SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
date Fri, 02 Apr 2010 14:53:32 -0400
parents 8de3bef71458
children 4306796d60a8
comparison
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318:8de3bef71458 319:7a12d2c3d06b
122 print('\n\n\tfinetune with P07\n\n') 122 print('\n\n\tfinetune with P07\n\n')
123 optimizer.reload_parameters('params_pretrain.txt') 123 optimizer.reload_parameters('params_pretrain.txt')
124 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=0) 124 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=0)
125 channel.save() 125 channel.save()
126 if finetune_choice == 2: 126 if finetune_choice == 2:
127 print('\n\n\tfinetune with NIST followed by P07\n\n') 127 print('\n\n\tfinetune with P07 followed by NIST\n\n')
128 optimizer.reload_parameters('params_pretrain.txt') 128 optimizer.reload_parameters('params_pretrain.txt')
129 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=20)
129 optimizer.finetune(datasets.nist_all(),datasets.nist_P07(),max_finetune_epoch_NIST,ind_test=21) 130 optimizer.finetune(datasets.nist_all(),datasets.nist_P07(),max_finetune_epoch_NIST,ind_test=21)
130 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=20)
131 channel.save() 131 channel.save()
132 if finetune_choice == 3: 132 if finetune_choice == 3:
133 print('\n\n\tfinetune with NIST only on the logistic regression on top (but validation on P07).\n\ 133 print('\n\n\tfinetune with NIST only on the logistic regression on top (but validation on P07).\n\
134 All hidden units output are input of the logistic regression\n\n') 134 All hidden units output are input of the logistic regression\n\n')
135 optimizer.reload_parameters('params_pretrain.txt') 135 optimizer.reload_parameters('params_pretrain.txt')
146 print('\n\n\tfinetune with P07\n\n') 146 print('\n\n\tfinetune with P07\n\n')
147 sys.stdout.flush() 147 sys.stdout.flush()
148 optimizer.reload_parameters('params_pretrain.txt') 148 optimizer.reload_parameters('params_pretrain.txt')
149 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=0) 149 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=0)
150 channel.save() 150 channel.save()
151 print('\n\n\tfinetune with NIST (done earlier) followed by P07 (written here)\n\n') 151 print('\n\n\tfinetune with P07 (done earlier) followed by NIST (written here)\n\n')
152 sys.stdout.flush() 152 sys.stdout.flush()
153 optimizer.reload_parameters('params_finetune_NIST.txt') 153 optimizer.reload_parameters('params_finetune_P07.txt')
154 optimizer.finetune(datasets.nist_P07(),datasets.nist_all(),max_finetune_epoch_P07,ind_test=20) 154 optimizer.finetune(datasets.nist_all(),datasets.nist_P07(),max_finetune_epoch_NIST,ind_test=21)
155 channel.save() 155 channel.save()
156 print('\n\n\tfinetune with NIST only on the logistic regression on top.\n\ 156 print('\n\n\tfinetune with NIST only on the logistic regression on top.\n\
157 All hidden units output are input of the logistic regression\n\n') 157 All hidden units output are input of the logistic regression\n\n')
158 sys.stdout.flush() 158 sys.stdout.flush()
159 optimizer.reload_parameters('params_pretrain.txt') 159 optimizer.reload_parameters('params_pretrain.txt')