==================== Environment Info ====================
Dataset Path: /workspace/data
===========================================================

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000940000 1000460000 4096 Oct 23 04:46 .
drwxrwsrwx. 4         99 1000460000 4096 Oct 23 04:46 ..
drwxr-sr-x. 3 1000940000 1000460000 4096 Oct 23 04:46 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1023 04:46:39.949000 3 torch/distributed/run.py:874] 
W1023 04:46:39.949000 3 torch/distributed/run.py:874] *****************************************
W1023 04:46:39.949000 3 torch/distributed/run.py:874] 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. 
W1023 04:46:39.949000 3 torch/distributed/run.py:874] *****************************************
2026-10-23T04:46:45Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-10-23T04:46:45Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-10-23T04:46:45Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-23T04:46:45Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-23T04:46:45Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.303004
2026-10-23T04:46:47Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 2.300645
2026-10-23T04:46:48Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 2.818543
2026-10-23T04:46:49Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 2.325322
2026-10-23T04:46:51Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 1.741063
2026-10-23T04:46:52Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 1.949269
2026-10-23T04:46:54Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 2.181565
2026-10-23T04:46:55Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.778751
2026-10-23T04:46:56Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.918966
2026-10-23T04:46:58Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.715470
2026-10-23T04:46:59Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.525421
2026-10-23T04:47:01Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.609992
2026-10-23T04:47:02Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.496159
2026-10-23T04:47:04Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.506513
2026-10-23T04:47:05Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.709589
2026-10-23T04:47:06Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.732061
2026-10-23T04:47:08Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.327875
2026-10-23T04:47:09Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.422134
2026-10-23T04:47:11Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.655987
2026-10-23T04:47:12Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.469268
2026-10-23T04:47:13Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.472108
2026-10-23T04:47:15Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.505851
2026-10-23T04:47:16Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.561116
2026-10-23T04:47:18Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.171174
2026-10-23T04:47:18Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.988389 | Batches: 235
2026-10-23T04:47:18Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 1.009176 | Batches: 235
2026-10-23T04:47:18Z INFO     [CPU0] Training is finished
2026-10-23T04:47:18Z INFO     [CPU1] Training is finished

==================== Training Complete ====================