Created by: llxxxll

python train.py I0326 23:52:29.501113 804 Util.cpp:160] commandline: --use_gpu=False --trainer_count=1 [INFO 2017-03-26 23:52:29,509 layers.py:2106] output for conv_0: c = 64, h = 32, w = 32, size = 65536 [INFO 2017-03-26 23:52:29,511 layers.py:2106] output for conv_1: c = 64, h = 32, w = 32, size = 65536 [INFO 2017-03-26 23:52:29,513 layers.py:2230] output for pool_0: c = 64, h = 16, w = 16, size = 16384 [INFO 2017-03-26 23:52:29,514 layers.py:2106] output for conv_2: c = 128, h = 16, w = 16, size = 32768 [INFO 2017-03-26 23:52:29,517 layers.py:2106] output for conv_3: c = 128, h = 16, w = 16, size = 32768 [INFO 2017-03-26 23:52:29,518 layers.py:2230] output for pool_1: c = 128, h = 8, w = 8, size = 8192 [INFO 2017-03-26 23:52:29,518 layers.py:2106] output for conv_4: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,519 layers.py:2106] output for conv_5: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,520 layers.py:2106] output for conv_6: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,521 layers.py:2230] output for pool_2: c = 256, h = 4, w = 4, size = 4096 [INFO 2017-03-26 23:52:29,522 layers.py:2106] output for conv_7: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,523 layers.py:2106] output for conv_8: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,524 layers.py:2106] output for conv_9: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,525 layers.py:2230] output for pool_3: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,526 layers.py:2106] output for conv_10: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,527 layers.py:2106] output for conv_11: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,528 layers.py:2106] output for conv_12: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,531 layers.py:2230] output for pool_4: c = 512, h = 1, w = 1, size = 512 [INFO 2017-03-26 23:52:29,534 networks.py:1472] The input order is [image, label] [INFO 2017-03-26 23:52:29,535 networks.py:1478] The output order is [classification_cost_0] [INFO 2017-03-26 23:52:29,536 layers.py:2106] output for conv_0: c = 64, h = 32, w = 32, size = 65536 [INFO 2017-03-26 23:52:29,537 layers.py:2106] output for conv_1: c = 64, h = 32, w = 32, size = 65536 [INFO 2017-03-26 23:52:29,539 layers.py:2230] output for pool_0: c = 64, h = 16, w = 16, size = 16384 [INFO 2017-03-26 23:52:29,539 layers.py:2106] output for conv_2: c = 128, h = 16, w = 16, size = 32768 [INFO 2017-03-26 23:52:29,540 layers.py:2106] output for conv_3: c = 128, h = 16, w = 16, size = 32768 [INFO 2017-03-26 23:52:29,541 layers.py:2230] output for pool_1: c = 128, h = 8, w = 8, size = 8192 [INFO 2017-03-26 23:52:29,542 layers.py:2106] output for conv_4: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,543 layers.py:2106] output for conv_5: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,544 layers.py:2106] output for conv_6: c = 256, h = 8, w = 8, size = 16384 [INFO 2017-03-26 23:52:29,546 layers.py:2230] output for pool_2: c = 256, h = 4, w = 4, size = 4096 [INFO 2017-03-26 23:52:29,547 layers.py:2106] output for conv_7: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,548 layers.py:2106] output for conv_8: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,549 layers.py:2106] output for conv_9: c = 512, h = 4, w = 4, size = 8192 [INFO 2017-03-26 23:52:29,552 layers.py:2230] output for pool_3: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,553 layers.py:2106] output for conv_10: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,555 layers.py:2106] output for conv_11: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,556 layers.py:2106] output for conv_12: c = 512, h = 2, w = 2, size = 2048 [INFO 2017-03-26 23:52:29,557 layers.py:2230] output for pool_4: c = 512, h = 1, w = 1, size = 512 [INFO 2017-03-26 23:52:29,559 networks.py:1472] The input order is [image, label] [INFO 2017-03-26 23:52:29,559 networks.py:1478] The output order is [classification_cost_0] I0326 23:52:29.609350 804 GradientMachine.cpp:86] Initing parameters.. I0326 23:52:30.362373 804 GradientMachine.cpp:93] Init parameters done. Killed