20e381edb4
updates
2020-01-20 22:43:37 -08:00
d3738f5330
updates
2020-01-19 16:56:32 -08:00
c91ffee852
updates
2020-01-19 16:55:29 -08:00
19f75f986d
updates
2020-01-19 16:54:49 -08:00
abbf9fa2d4
updates
2020-01-19 15:37:56 -08:00
51b5b3288f
updates
2020-01-19 14:59:07 -08:00
3d1db0b5ac
updates
2020-01-19 11:37:12 -08:00
43956d6305
updates
2020-01-17 23:30:17 -08:00
3bac3c63b1
updates
2020-01-17 19:42:04 -08:00
bab855507a
updates
2020-01-17 18:05:28 -08:00
a4b8815ed9
updates
2020-01-17 17:58:37 -08:00
dec2c7d9a6
updates
2020-01-17 17:52:28 -08:00
1ba9bd746b
updates
2020-01-17 11:17:52 -08:00
831d2b3dcc
updates
2020-01-17 11:17:18 -08:00
a8e1390028
updates
2020-01-17 10:55:30 -08:00
5831d2d6ba
updates
2020-01-15 09:28:58 -08:00
01dbdc45d7
updates
2020-01-14 22:22:24 -08:00
25ccf54a94
updates
2020-01-12 17:05:03 -08:00
33264f5567
updates
2020-01-12 16:18:29 -08:00
5ac3eb42b6
updates
2020-01-12 15:56:42 -08:00
01d485831f
updates
2020-01-11 20:15:41 -08:00
fc0748f876
updates
2020-01-10 23:28:54 -08:00
ba265d91b2
updates
2020-01-10 16:09:36 -08:00
c8a67adecc
updates
2020-01-10 12:49:22 -08:00
3b1caf9a43
updates
2020-01-06 11:57:12 -08:00
04a0a6f609
updates
2020-01-05 12:50:58 -08:00
efe3c319b5
updates
2020-01-03 18:06:59 -08:00
07c40a3f14
updates
2020-01-03 14:36:39 -08:00
4fe9c90514
updates
2020-01-03 11:53:02 -08:00
eca1a25dcd
updates
2020-01-03 09:19:18 -08:00
6290f9fdb7
updates
2019-12-30 16:13:06 -08:00
9e58191983
updates
2019-12-30 13:31:32 -08:00
017a5ddad0
updates
2019-12-30 13:28:46 -08:00
e5b5d6a880
updates
2019-12-27 14:58:31 -08:00
162ddcf6c7
updates
2019-12-27 13:04:46 -08:00
4843cc4e08
updates
2019-12-27 12:52:01 -08:00
56d7261083
updates
2019-12-27 10:52:19 -08:00
2fe6c21ce8
updates
2019-12-27 09:28:10 -08:00
4bbed32f01
updates
2019-12-27 08:10:05 -08:00
8ae06ad7c3
updates
2019-12-25 19:58:20 -08:00
3c4e7751ed
updates
2019-12-24 13:11:01 -08:00
ba24e26f7e
updates
2019-12-23 15:43:00 -08:00
c459bc6d4a
updates
2019-12-23 12:11:37 -08:00
6946a2a8fc
updates
2019-12-23 11:14:34 -08:00
d391f6d59b
updates
2019-12-22 17:36:51 -08:00
f00de54546
updates
2019-12-21 20:17:56 -08:00
acdbaa7702
updates
2019-12-21 19:56:52 -08:00
5e203d3b1a
updates
2019-12-21 19:48:07 -08:00
b7a53957b3
updates
2019-12-21 19:47:49 -08:00
69da7e9da5
updates
2019-12-21 12:00:16 -08:00
2bc6683325
updates
2019-12-20 09:07:25 -08:00
ad73ce4334
updates
2019-12-18 10:24:10 -08:00
8385f613d2
updates
2019-12-18 09:45:34 -08:00
87c5e43e8c
updates
2019-12-15 12:47:53 -08:00
d884c33d21
updates
2019-12-15 12:43:30 -08:00
8c13717f48
updates
2019-12-14 15:40:01 -08:00
1bb738c83f
updates
2019-12-13 11:49:29 -08:00
61c3cb9ecf
updates
2019-12-08 17:57:23 -08:00
e35397ee41
updates
2019-12-08 17:52:44 -08:00
267367b105
updates
2019-12-08 16:34:27 -08:00
0fa4e498c1
updates
2019-12-08 16:34:01 -08:00
b81beb0f5f
updates
2019-12-07 22:55:26 -08:00
1f943e886f
updates
2019-12-07 15:17:29 -08:00
55ba979816
updates
2019-12-07 01:26:41 -08:00
bb54408f73
updates
2019-12-07 00:05:37 -08:00
d5176e4fc4
updates
2019-12-07 00:01:18 -08:00
2c0985f366
updates
2019-12-06 23:58:47 -08:00
a066a7b8ea
updates
2019-12-06 19:05:51 -08:00
63c2736c12
updates
2019-12-04 23:02:32 -08:00
0a04eb9ff1
updates
2019-12-04 15:15:42 -08:00
a2dc8a6b5a
updates
2019-12-04 15:15:23 -08:00
93a70d958a
updates
2019-12-02 11:31:19 -08:00
3d91731519
updates
2019-12-01 14:07:09 -08:00
e637ae44dd
updates
2019-12-01 14:06:11 -08:00
d6a7a614dc
updates
2019-12-01 13:51:55 -08:00
92690302bb
updates
2019-12-01 13:49:38 -08:00
e613bbc88c
updates
2019-11-29 19:10:01 -08:00
9e9a6a1425
updates
2019-11-27 15:50:29 -10:00
82b62c9855
updates
2019-11-27 15:50:00 -10:00
3c57ff7b1b
updates
2019-11-25 17:24:05 -10:00
75e8ec323f
updates
2019-11-25 11:45:28 -10:00
26e3a28bee
Update train.py for distributive programming ( #655 )
...
When attempting to running this function in a multi-GPU environment I kept on getting a runtime issue. I was able to solve this problem by passing this keyword. I first found the solution here:
https://github.com/pytorch/pytorch/issues/22436
and in the pytorch tutorial
'RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by (1) passing the keyword argument find_unused_parameters=True to torch.nn.parallel.DistributedDataParallel; (2) making sure all forward function outputs participate in calculating loss. If you already have done the above two steps, then the distributed data parallel module wasn't able to locate the output tensors in the return value of your module's forward function. Please include the loss function and the structure of the return value of forward of your module when reporting this issue (e.g. list, dict, iterable). '
2019-11-24 22:21:36 -10:00
7773651e8e
updates
2019-11-24 18:38:30 -10:00
f12a2a513a
updates
2019-11-24 18:29:29 -10:00
f38723c0bd
updates
2019-11-20 19:34:22 -08:00
3a4ed8b3ab
updates
2019-11-20 13:40:24 -08:00
bb209111c4
updates
2019-11-20 13:36:15 -08:00
8e327e3bd0
updates
2019-11-20 13:33:25 -08:00
2950f4c816
updates
2019-11-20 13:26:50 -08:00
c14ea59c71
updates
2019-11-20 13:24:50 -08:00
bd498ae776
updates
2019-11-20 13:14:24 -08:00
e58f0a68b6
updates
2019-11-20 12:05:40 -08:00
d355e539d9
updates
2019-11-19 18:47:22 -08:00
d9805d2fb6
updates
2019-11-19 12:42:12 -08:00
2ba1a4c9cc
updates
2019-11-18 12:01:17 -08:00
9c716a39c3
updates
2019-11-17 19:00:12 -08:00
a1151c04a7
updates
2019-11-17 18:48:50 -08:00
fe9ade6a64
updates
2019-11-16 12:07:19 -08:00
985006a52a
updates
2019-11-14 17:25:29 -08:00
9daa5e858a
updates
2019-11-14 17:22:09 -08:00
Glenn Jocher
Francisco Reveriano