Subject | Hash | Author | Date (UTC) |
---|---|---|---|
change optim to Adam, lr and decay same with content aware network | 0b0879b22e9d202015e67a0cc8c87ddcafb3c2d2 | Thai Thien | 2020-02-28 17:15:05 |
train with higher learning rate | 3fa7e328dc4b7b4570fd32908b3df5fab8283919 | Thai Thien | 2020-02-28 16:57:16 |
train 25 epoch only | 1cfb58b5eae299f49e3b64289c3a12a8f35cee45 | Thai Thien | 2020-02-27 18:35:58 |
we freeze vgg pretrain layer | 459cefbfbf53949cb9636ca002cd4f78e964bb83 | Thai Thien | 2020-02-27 18:24:17 |
fix error when save | 86a8f467d47a67da0accc963e8baacbaea07ab14 | Thai Thien | 2020-02-27 17:55:46 |
we discard deform 7 and keep deform 5 instead | 91ff78e4a1aef3677b15447b631c2927c9e62a31 | Thai Thien | 2020-02-27 16:22:47 |
reduce image by crop | 530516ff40b744cac79756c97faaed50c8b65cfb | Thai Thien | 2020-02-27 16:19:11 |
try to solve x8/8 dimension mismatch | 6b0616197995b3c95041cde43030245f96f1f81e | Thai Thien | 2020-02-27 16:17:12 |
reduce model size, discard middle deform (kernal size 5) | 00fb477cf699a8f2eed8e861f241c077b2046000 | Thai Thien | 2020-02-27 16:11:51 |
shanghaitech same size density map | 25fc2e9395dd67bb6cc273c7fe6cd64c3b154120 | Thai Thien | 2020-02-27 16:03:05 |
fix target1.unsqueeze(0) | bb5c46f121207fd9838ee085314df40513e2ed32 | Thai Thien | 2020-02-27 15:56:07 |
because GPU too small, we crop shanghaitech A | 0f97517dd8de5d3d75cf49af9aa9d20e4595ea3e | Thai Thien | 2020-02-27 15:52:21 |
meow | 3b9576511e597b4894c7c95ca06dc5219ef9c524 | tthien | 2020-02-27 15:44:39 |
fix wrong py name in script, dataset use only 1 worker | 3bd765c9aa79e47049a94547e57deb68c947001c | Thai Thien | 2020-02-27 15:41:44 |
minor fix | 5505b9a8b28df105e11a99d3462323ae9d507102 | Thai Thien | 2020-02-27 15:28:37 |
get ready for short training run with 30 epochs | 66dda0858561897cd5f81e10077459adb39d86dd | Thai Thien | 2020-02-27 15:22:01 |
implement attn_can_adcrowdnet | ffd38664a43d861c20cdc225746b9ce2a00260c7 | Thai Thien | 2020-02-27 15:10:27 |
WIP: add can-adcrowdnet | 5620b83449b31d00a367c8de77e431e19a5ccfb3 | Thai Thien | 2020-02-25 11:31:38 |
add readable timestamp viz | ae1fdb49ddb9ea77659529dceb7fb87c2790c8dc | Thai Thien | 2020-02-24 03:49:57 |
change save name prefix | c53a86f30fb8fd4e8f3a409eb67827d56a43ae5c | Thai Thien | 2020-02-02 10:48:15 |
File | Lines added | Lines deleted |
---|---|---|
train_attn_can_adcrowdnet_freeze_vgg.py | 1 | 2 |
train_script/attn_can_adcrowdnet/train_server_31_epoch_shA_freeze_vgg.sh | 1 | 0 |
File train_attn_can_adcrowdnet_freeze_vgg.py changed (mode: 100644) (index de7e0fb..e47bfc7) | |||
... | ... | if __name__ == "__main__": | |
38 | 38 | # loss function | # loss function |
39 | 39 | loss_fn = nn.MSELoss(size_average=False).to(device) | loss_fn = nn.MSELoss(size_average=False).to(device) |
40 | 40 | ||
41 | optimizer = torch.optim.SGD(model.parameters(), args.lr, | ||
42 | momentum=args.momentum, | ||
41 | optimizer = torch.optim.Adam(model.parameters(), args.lr, | ||
43 | 42 | weight_decay=args.decay) | weight_decay=args.decay) |
44 | 43 | ||
45 | 44 | trainer = create_supervised_trainer(model, optimizer, loss_fn, device=device) | trainer = create_supervised_trainer(model, optimizer, loss_fn, device=device) |
File train_script/attn_can_adcrowdnet/train_server_31_epoch_shA_freeze_vgg.sh changed (mode: 100644) (index 5ceb244..cb7dac6) | |||
... | ... | CUDA_VISIBLE_DEVICES=5 nohup python train_attn_can_adcrowdnet_freeze_vgg.py \ | |
10 | 10 | --task_id attn_can_adcrowdnet_default_shtA_33_freeze_vgg_2 \ | --task_id attn_can_adcrowdnet_default_shtA_33_freeze_vgg_2 \ |
11 | 11 | --input /data/rnd/thient/thient_data/ShanghaiTech/part_A \ | --input /data/rnd/thient/thient_data/ShanghaiTech/part_A \ |
12 | 12 | --lr 1e-4 \ | --lr 1e-4 \ |
13 | --decay 5*1e-4 \ | ||
13 | 14 | --datasetname shanghaitech \ | --datasetname shanghaitech \ |
14 | 15 | --epochs 33 > logs/attn_can_adcrowdnet_default_shtA_33_freeze_vgg_2.log & | --epochs 33 > logs/attn_can_adcrowdnet_default_shtA_33_freeze_vgg_2.log & |