File size: 22,086 Bytes
3650590 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 | [2025-05-03 19:17:10,547] torch.distributed.run: [WARNING] master_addr is only used for static rdzv_backend and when rdzv_endpoint is not specified.
[2025-05-03 19:17:10,547] torch.distributed.run: [WARNING]
[2025-05-03 19:17:10,547] torch.distributed.run: [WARNING] *****************************************
[2025-05-03 19:17:10,547] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
[2025-05-03 19:17:10,547] torch.distributed.run: [WARNING] *****************************************
[[34m2025-05-03 19:17:13[0m] Experiment directory created at logs/nwm_cdit_m
[[34m2025-05-03 19:17:27[0m] CDiT Parameters: 1,011,959,456
[[34m2025-05-03 19:17:28[0m] Dataset contains 132,929 images
[[34m2025-05-03 19:17:28[0m] Training for 300 epochs...
[[34m2025-05-03 19:17:28[0m] Beginning epoch 0...
[[34m2025-05-03 19:20:24[0m] (step=0000100) Train Loss: 0.3427, Train Steps/Sec: 0.57, Samples/Sec: 27.26
[[34m2025-05-03 19:21:10[0m] (step=0000200) Train Loss: 0.2083, Train Steps/Sec: 2.15, Samples/Sec: 103.05
[[34m2025-05-03 19:21:57[0m] (step=0000300) Train Loss: 0.1963, Train Steps/Sec: 2.15, Samples/Sec: 103.02
[[34m2025-05-03 19:22:45[0m] (step=0000400) Train Loss: 0.1902, Train Steps/Sec: 2.10, Samples/Sec: 100.83
[[34m2025-05-03 19:23:31[0m] (step=0000500) Train Loss: 0.1773, Train Steps/Sec: 2.14, Samples/Sec: 102.95
[[34m2025-05-03 19:24:18[0m] (step=0000600) Train Loss: 0.1827, Train Steps/Sec: 2.15, Samples/Sec: 103.03
[[34m2025-05-03 19:25:04[0m] (step=0000700) Train Loss: 0.1773, Train Steps/Sec: 2.14, Samples/Sec: 102.95
[[34m2025-05-03 19:25:51[0m] (step=0000800) Train Loss: 0.1689, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:26:38[0m] (step=0000900) Train Loss: 0.1784, Train Steps/Sec: 2.15, Samples/Sec: 102.99
[[34m2025-05-03 19:27:25[0m] (step=0001000) Train Loss: 0.1725, Train Steps/Sec: 2.13, Samples/Sec: 102.40
[[34m2025-05-03 19:28:12[0m] (step=0001100) Train Loss: 0.1645, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:28:58[0m] (step=0001200) Train Loss: 0.1716, Train Steps/Sec: 2.13, Samples/Sec: 102.41
[[34m2025-05-03 19:29:45[0m] (step=0001300) Train Loss: 0.1750, Train Steps/Sec: 2.15, Samples/Sec: 103.04
[[34m2025-05-03 19:30:32[0m] (step=0001400) Train Loss: 0.1631, Train Steps/Sec: 2.15, Samples/Sec: 102.98
[[34m2025-05-03 19:31:19[0m] (step=0001500) Train Loss: 0.1667, Train Steps/Sec: 2.12, Samples/Sec: 101.82
[[34m2025-05-03 19:32:06[0m] (step=0001600) Train Loss: 0.1680, Train Steps/Sec: 2.15, Samples/Sec: 102.99
[[34m2025-05-03 19:32:52[0m] (step=0001700) Train Loss: 0.1665, Train Steps/Sec: 2.15, Samples/Sec: 103.03
[[34m2025-05-03 19:33:39[0m] (step=0001800) Train Loss: 0.1602, Train Steps/Sec: 2.15, Samples/Sec: 102.99
[[34m2025-05-03 19:34:26[0m] (step=0001900) Train Loss: 0.1718, Train Steps/Sec: 2.12, Samples/Sec: 101.97
[[34m2025-05-03 19:35:12[0m] (step=0002000) Train Loss: 0.1734, Train Steps/Sec: 2.15, Samples/Sec: 102.98
[[34m2025-05-03 19:35:29[0m] Saved checkpoint to logs/nwm_cdit_m/checkpoints/latest.pth.tar
[[34m2025-05-03 19:36:16[0m] (step=0002100) Train Loss: 0.1608, Train Steps/Sec: 1.59, Samples/Sec: 76.15
[[34m2025-05-03 19:37:02[0m] (step=0002200) Train Loss: 0.1668, Train Steps/Sec: 2.15, Samples/Sec: 103.05
[[34m2025-05-03 19:37:49[0m] (step=0002300) Train Loss: 0.1628, Train Steps/Sec: 2.13, Samples/Sec: 102.43
[[34m2025-05-03 19:38:36[0m] (step=0002400) Train Loss: 0.1686, Train Steps/Sec: 2.13, Samples/Sec: 102.36
[[34m2025-05-03 19:39:23[0m] (step=0002500) Train Loss: 0.1595, Train Steps/Sec: 2.13, Samples/Sec: 102.36
[[34m2025-05-03 19:40:09[0m] (step=0002600) Train Loss: 0.1698, Train Steps/Sec: 2.14, Samples/Sec: 102.95
[[34m2025-05-03 19:40:56[0m] (step=0002700) Train Loss: 0.1662, Train Steps/Sec: 2.14, Samples/Sec: 102.55
[[34m2025-05-03 19:41:43[0m] (step=0002800) Train Loss: 0.1591, Train Steps/Sec: 2.15, Samples/Sec: 103.00
[[34m2025-05-03 19:42:30[0m] (step=0002900) Train Loss: 0.1673, Train Steps/Sec: 2.12, Samples/Sec: 101.75
[[34m2025-05-03 19:43:17[0m] (step=0003000) Train Loss: 0.1561, Train Steps/Sec: 2.15, Samples/Sec: 102.97
[[34m2025-05-03 19:44:03[0m] (step=0003100) Train Loss: 0.1615, Train Steps/Sec: 2.15, Samples/Sec: 103.00
[[34m2025-05-03 19:44:50[0m] (step=0003200) Train Loss: 0.1586, Train Steps/Sec: 2.14, Samples/Sec: 102.50
[[34m2025-05-03 19:45:37[0m] (step=0003300) Train Loss: 0.1537, Train Steps/Sec: 2.12, Samples/Sec: 101.82
[[34m2025-05-03 19:46:24[0m] (step=0003400) Train Loss: 0.1555, Train Steps/Sec: 2.14, Samples/Sec: 102.96
[[34m2025-05-03 19:47:10[0m] (step=0003500) Train Loss: 0.1598, Train Steps/Sec: 2.15, Samples/Sec: 103.00
[[34m2025-05-03 19:47:57[0m] (step=0003600) Train Loss: 0.1564, Train Steps/Sec: 2.14, Samples/Sec: 102.58
[[34m2025-05-03 19:48:44[0m] (step=0003700) Train Loss: 0.1616, Train Steps/Sec: 2.13, Samples/Sec: 102.32
[[34m2025-05-03 19:49:31[0m] (step=0003800) Train Loss: 0.1593, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:50:18[0m] (step=0003900) Train Loss: 0.1575, Train Steps/Sec: 2.14, Samples/Sec: 102.94
[[34m2025-05-03 19:51:04[0m] (step=0004000) Train Loss: 0.1603, Train Steps/Sec: 2.13, Samples/Sec: 102.37
[[34m2025-05-03 19:51:19[0m] Saved checkpoint to logs/nwm_cdit_m/checkpoints/latest.pth.tar
[[34m2025-05-03 19:52:06[0m] (step=0004100) Train Loss: 0.1566, Train Steps/Sec: 1.62, Samples/Sec: 77.61
[[34m2025-05-03 19:52:53[0m] (step=0004200) Train Loss: 0.1528, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:53:40[0m] (step=0004300) Train Loss: 0.1591, Train Steps/Sec: 2.15, Samples/Sec: 102.97
[[34m2025-05-03 19:54:27[0m] (step=0004400) Train Loss: 0.1582, Train Steps/Sec: 2.14, Samples/Sec: 102.53
[[34m2025-05-03 19:55:13[0m] (step=0004500) Train Loss: 0.1539, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:56:00[0m] (step=0004600) Train Loss: 0.1567, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 19:56:47[0m] (step=0004700) Train Loss: 0.1534, Train Steps/Sec: 2.15, Samples/Sec: 103.05
[[34m2025-05-03 19:57:33[0m] (step=0004800) Train Loss: 0.1592, Train Steps/Sec: 2.15, Samples/Sec: 103.00
[[34m2025-05-03 19:58:20[0m] (step=0004900) Train Loss: 0.1558, Train Steps/Sec: 2.13, Samples/Sec: 102.47
[[34m2025-05-03 19:59:07[0m] (step=0005000) Train Loss: 0.1563, Train Steps/Sec: 2.12, Samples/Sec: 101.89
[[34m2025-05-03 19:59:54[0m] (step=0005100) Train Loss: 0.1567, Train Steps/Sec: 2.15, Samples/Sec: 103.02
[[34m2025-05-03 20:00:41[0m] (step=0005200) Train Loss: 0.1473, Train Steps/Sec: 2.15, Samples/Sec: 103.10
[[34m2025-05-03 20:01:27[0m] (step=0005300) Train Loss: 0.1503, Train Steps/Sec: 2.13, Samples/Sec: 102.40
[[34m2025-05-03 20:02:14[0m] (step=0005400) Train Loss: 0.1573, Train Steps/Sec: 2.13, Samples/Sec: 102.44
[[34m2025-05-03 20:03:01[0m] (step=0005500) Train Loss: 0.1503, Train Steps/Sec: 2.14, Samples/Sec: 102.49
[[34m2025-05-03 20:03:48[0m] (step=0005600) Train Loss: 0.1553, Train Steps/Sec: 2.15, Samples/Sec: 103.02
[[34m2025-05-03 20:04:35[0m] (step=0005700) Train Loss: 0.1517, Train Steps/Sec: 2.14, Samples/Sec: 102.55
[[34m2025-05-03 20:05:21[0m] (step=0005800) Train Loss: 0.1590, Train Steps/Sec: 2.13, Samples/Sec: 102.40
[[34m2025-05-03 20:06:08[0m] (step=0005900) Train Loss: 0.1487, Train Steps/Sec: 2.13, Samples/Sec: 102.44
[[34m2025-05-03 20:06:55[0m] (step=0006000) Train Loss: 0.1486, Train Steps/Sec: 2.14, Samples/Sec: 102.92
[[34m2025-05-03 20:07:10[0m] Saved checkpoint to logs/nwm_cdit_m/checkpoints/latest.pth.tar
[[34m2025-05-03 20:07:57[0m] (step=0006100) Train Loss: 0.1519, Train Steps/Sec: 1.61, Samples/Sec: 77.30
[[34m2025-05-03 20:08:44[0m] (step=0006200) Train Loss: 0.1544, Train Steps/Sec: 2.15, Samples/Sec: 103.04
[[34m2025-05-03 20:09:31[0m] (step=0006300) Train Loss: 0.1520, Train Steps/Sec: 2.13, Samples/Sec: 102.01
[[34m2025-05-03 20:10:17[0m] (step=0006400) Train Loss: 0.1439, Train Steps/Sec: 2.15, Samples/Sec: 103.02
[[34m2025-05-03 20:11:04[0m] (step=0006500) Train Loss: 0.1527, Train Steps/Sec: 2.15, Samples/Sec: 103.01
[[34m2025-05-03 20:11:51[0m] (step=0006600) Train Loss: 0.1510, Train Steps/Sec: 2.13, Samples/Sec: 102.31
[[34m2025-05-03 20:12:38[0m] (step=0006700) Train Loss: 0.1495, Train Steps/Sec: 2.12, Samples/Sec: 101.83
[[34m2025-05-03 20:13:25[0m] (step=0006800) Train Loss: 0.1514, Train Steps/Sec: 2.15, Samples/Sec: 102.98
[[34m2025-05-03 20:14:11[0m] (step=0006900) Train Loss: 0.1505, Train Steps/Sec: 2.14, Samples/Sec: 102.89
[[34m2025-05-03 20:14:58[0m] (step=0007000) Train Loss: 0.1450, Train Steps/Sec: 2.13, Samples/Sec: 102.45
[[34m2025-05-03 20:15:45[0m] (step=0007100) Train Loss: 0.1522, Train Steps/Sec: 2.15, Samples/Sec: 103.02
[[34m2025-05-03 20:16:32[0m] (step=0007200) Train Loss: 0.1496, Train Steps/Sec: 2.12, Samples/Sec: 101.90
[[34m2025-05-03 20:17:18[0m] (step=0007300) Train Loss: 0.1483, Train Steps/Sec: 2.15, Samples/Sec: 103.08
[[34m2025-05-03 20:18:05[0m] (step=0007400) Train Loss: 0.1457, Train Steps/Sec: 2.14, Samples/Sec: 102.48
[[34m2025-05-03 20:18:52[0m] (step=0007500) Train Loss: 0.1514, Train Steps/Sec: 2.15, Samples/Sec: 103.07
[[34m2025-05-03 20:19:39[0m] (step=0007600) Train Loss: 0.1475, Train Steps/Sec: 2.12, Samples/Sec: 101.98
[[34m2025-05-03 20:20:25[0m] (step=0007700) Train Loss: 0.1506, Train Steps/Sec: 2.15, Samples/Sec: 103.07
[[34m2025-05-03 20:21:12[0m] (step=0007800) Train Loss: 0.1528, Train Steps/Sec: 2.14, Samples/Sec: 102.50
[[34m2025-05-03 20:21:59[0m] (step=0007900) Train Loss: 0.1442, Train Steps/Sec: 2.15, Samples/Sec: 103.03
[[34m2025-05-03 20:22:46[0m] (step=0008000) Train Loss: 0.1514, Train Steps/Sec: 2.12, Samples/Sec: 101.91
[[34m2025-05-03 20:23:01[0m] Saved checkpoint to logs/nwm_cdit_m/checkpoints/latest.pth.tar
[[34m2025-05-03 20:23:47[0m] (step=0008100) Train Loss: 0.1502, Train Steps/Sec: 1.62, Samples/Sec: 77.90
[[34m2025-05-03 20:24:34[0m] (step=0008200) Train Loss: 0.1422, Train Steps/Sec: 2.15, Samples/Sec: 103.09
[[34m2025-05-03 20:25:21[0m] (step=0008300) Train Loss: 0.1492, Train Steps/Sec: 2.14, Samples/Sec: 102.51
[[34m2025-05-03 20:26:08[0m] (step=0008400) Train Loss: 0.1483, Train Steps/Sec: 2.12, Samples/Sec: 101.88
[[34m2025-05-03 20:26:55[0m] (step=0008500) Train Loss: 0.1516, Train Steps/Sec: 2.14, Samples/Sec: 102.96
[[34m2025-05-03 20:27:41[0m] (step=0008600) Train Loss: 0.1456, Train Steps/Sec: 2.15, Samples/Sec: 103.13
[[34m2025-05-03 20:28:28[0m] (step=0008700) Train Loss: 0.1442, Train Steps/Sec: 2.13, Samples/Sec: 102.47
[[34m2025-05-03 20:29:15[0m] (step=0008800) Train Loss: 0.1426, Train Steps/Sec: 2.13, Samples/Sec: 102.42
[[34m2025-05-03 20:30:02[0m] (step=0008900) Train Loss: 0.1527, Train Steps/Sec: 2.14, Samples/Sec: 102.51
[[34m2025-05-03 20:30:48[0m] (step=0009000) Train Loss: 0.1414, Train Steps/Sec: 2.15, Samples/Sec: 103.05
[[34m2025-05-03 20:31:35[0m] (step=0009100) Train Loss: 0.1405, Train Steps/Sec: 2.13, Samples/Sec: 102.41
[[34m2025-05-03 20:32:22[0m] (step=0009200) Train Loss: 0.1449, Train Steps/Sec: 2.14, Samples/Sec: 102.53
[[34m2025-05-03 20:33:09[0m] (step=0009300) Train Loss: 0.1420, Train Steps/Sec: 2.13, Samples/Sec: 102.41
[[34m2025-05-03 20:33:55[0m] (step=0009400) Train Loss: 0.1454, Train Steps/Sec: 2.15, Samples/Sec: 103.00
[[34m2025-05-03 20:34:42[0m] (step=0009500) Train Loss: 0.1462, Train Steps/Sec: 2.14, Samples/Sec: 102.50
[[34m2025-05-03 20:35:29[0m] (step=0009600) Train Loss: 0.1490, Train Steps/Sec: 2.14, Samples/Sec: 102.90
[[34m2025-05-03 20:36:16[0m] (step=0009700) Train Loss: 0.1443, Train Steps/Sec: 2.12, Samples/Sec: 101.84
[[34m2025-05-03 20:37:03[0m] (step=0009800) Train Loss: 0.1417, Train Steps/Sec: 2.14, Samples/Sec: 102.87
[[34m2025-05-03 20:37:50[0m] (step=0009900) Train Loss: 0.1448, Train Steps/Sec: 2.13, Samples/Sec: 102.34
[[34m2025-05-03 20:38:36[0m] (step=0010000) Train Loss: 0.1431, Train Steps/Sec: 2.15, Samples/Sec: 103.01
Downloading: "https://github.com/facebookresearch/dino/zipball/main" to ./models/main.zip
Downloading: "https://github.com/facebookresearch/dino/zipball/main" to ./models/main.zip
[[34m2025-05-03 20:38:52[0m] Saved checkpoint to logs/nwm_cdit_m/checkpoints/latest.pth.tar
Downloading: "https://github.com/facebookresearch/dino/zipball/main" to ./models/main.zip
Traceback (most recent call last):
File "train.py", line 437, in <module>
main(args)
File "train.py", line 352, in main
sim_score = evaluate(ema, tokenizer, diffusion, test_dataset, rank, config["batch_size"], config["num_workers"], latent_size, device, save_dir, args.global_seed, bfloat_enable, num_cond)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "train.py", line 384, in evaluate
eval_model, _ = dreamsim(pretrained=True)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/model.py", line 275, in dreamsim
ours_model = PerceptualModel(**dreamsim_args['model_config'][dreamsim_type], device=device, load_dir=cache_dir,
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/model.py", line 65, in __init__
ViTExtractor(model_type, stride, load_dir, device=device)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/feature_extraction/extractor.py", line 44, in __init__
self.model = ViTExtractor.create_model(model_type, load_dir)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/feature_extraction/extractor.py", line 72, in create_model
model = torch.hub.load('facebookresearch/dino:main', model_type)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 563, in load
repo_or_dir = _get_cache_or_reload(repo_or_dir, force_reload, trust_repo, "load",
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 238, in _get_cache_or_reload
download_url_to_file(url, cached_file, progress=False)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 620, in download_url_to_file
u = urlopen(req)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 222, in urlopen
return opener.open(url, data, timeout)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 525, in open
response = self._open(req, data)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 542, in _open
result = self._call_chain(self.handle_open, protocol, protocol +
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 502, in _call_chain
result = func(*args)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 1397, in https_open
return self.do_open(http.client.HTTPSConnection, req,
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 1358, in do_open
r = h.getresponse()
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1348, in getresponse
response.begin()
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 316, in begin
version, status, reason = self._read_status()
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 285, in _read_status
raise RemoteDisconnected("Remote end closed connection without"
http.client.RemoteDisconnected: Remote end closed connection without response
Traceback (most recent call last):
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 1354, in do_open
h.request(req.get_method(), req.selector, req.data, headers,
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1256, in request
self._send_request(method, url, body, headers, encode_chunked)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1302, in _send_request
self.endheaders(body, encode_chunked=encode_chunked)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1251, in endheaders
self._send_output(message_body, encode_chunked=encode_chunked)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1011, in _send_output
self.send(msg)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 951, in send
self.connect()
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 1418, in connect
super().connect()
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/http/client.py", line 922, in connect
self.sock = self._create_connection(
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/socket.py", line 820, in create_connection
raise err
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/socket.py", line 808, in create_connection
sock.connect(sa)
TimeoutError: [Errno 110] Connection timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 437, in <module>
main(args)
File "train.py", line 352, in main
sim_score = evaluate(ema, tokenizer, diffusion, test_dataset, rank, config["batch_size"], config["num_workers"], latent_size, device, save_dir, args.global_seed, bfloat_enable, num_cond)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "train.py", line 384, in evaluate
eval_model, _ = dreamsim(pretrained=True)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/model.py", line 275, in dreamsim
ours_model = PerceptualModel(**dreamsim_args['model_config'][dreamsim_type], device=device, load_dir=cache_dir,
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/model.py", line 65, in __init__
ViTExtractor(model_type, stride, load_dir, device=device)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/feature_extraction/extractor.py", line 44, in __init__
self.model = ViTExtractor.create_model(model_type, load_dir)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/dreamsim/feature_extraction/extractor.py", line 72, in create_model
model = torch.hub.load('facebookresearch/dino:main', model_type)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 563, in load
repo_or_dir = _get_cache_or_reload(repo_or_dir, force_reload, trust_repo, "load",
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 238, in _get_cache_or_reload
download_url_to_file(url, cached_file, progress=False)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/hub.py", line 620, in download_url_to_file
u = urlopen(req)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 222, in urlopen
return opener.open(url, data, timeout)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 525, in open
response = self._open(req, data)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 542, in _open
result = self._call_chain(self.handle_open, protocol, protocol +
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 502, in _call_chain
result = func(*args)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 1397, in https_open
return self.do_open(http.client.HTTPSConnection, req,
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/urllib/request.py", line 1357, in do_open
raise URLError(err)
urllib.error.URLError: <urlopen error [Errno 110] Connection timed out>
[2025-05-03 20:41:14,779] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 715331 closing signal SIGTERM
[2025-05-03 20:41:14,780] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 715440 closing signal SIGTERM
[2025-05-03 20:41:14,944] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 2 (pid: 715461) of binary: /data1/zwc/miniconda3/envs/nwm2/bin/python
Traceback (most recent call last):
File "/data1/tpz/anaconda3/envs/nwm2/bin/torchrun", line 8, in <module>
sys.exit(main())
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper
return f(*args, **kwargs)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/distributed/run.py", line 806, in main
run(args)
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/distributed/run.py", line 797, in run
elastic_launch(
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
return launch_agent(self._config, self._entrypoint, list(args))
File "/data1/zwc/miniconda3/envs/nwm2/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
train.py FAILED
------------------------------------------------------------
Failures:
<NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2025-05-03_20:41:14
host : localhost
rank : 2 (local_rank: 2)
exitcode : 1 (pid: 715461)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
|