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

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000950000 1000280000 4096 Oct 30 07:52 .
drwxrwsrwx. 4         99 1000280000 4096 Oct 30 07:52 ..
drwxr-sr-x. 3 1000950000 1000280000 4096 Oct 30 07:52 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1030 07:52:28.450000 3 torch/distributed/run.py:874] 
W1030 07:52:28.450000 3 torch/distributed/run.py:874] *****************************************
W1030 07:52:28.450000 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. 
W1030 07:52:28.450000 3 torch/distributed/run.py:874] *****************************************
2026-10-30T07:53:42Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-10-30T07:53:42Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-10-30T07:53:42Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T07:53:42Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T07:53:42Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.314012
2026-10-30T07:53:44Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 2.041557
2026-10-30T07:53:45Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 1.034359
2026-10-30T07:53:46Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 0.857619
2026-10-30T07:53:47Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 0.875219
2026-10-30T07:53:48Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 0.584884
2026-10-30T07:53:50Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 0.363879
2026-10-30T07:53:51Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.493683
2026-10-30T07:53:52Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.594015
2026-10-30T07:53:53Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.406887
2026-10-30T07:53:54Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.329481
2026-10-30T07:53:55Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.434574
2026-10-30T07:53:57Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.313177
2026-10-30T07:53:58Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.322655
2026-10-30T07:53:59Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.577863
2026-10-30T07:54:00Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.629155
2026-10-30T07:54:01Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.346152
2026-10-30T07:54:02Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.420289
2026-10-30T07:54:04Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.536686
2026-10-30T07:54:05Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.478656
2026-10-30T07:54:06Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.420192
2026-10-30T07:54:07Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.432748
2026-10-30T07:54:08Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.543247
2026-10-30T07:54:10Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.142285
2026-10-30T07:54:10Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 0.632247 | Batches: 235
2026-10-30T07:54:10Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.625963 | Batches: 235
2026-10-30T07:54:10Z INFO     [CPU1] Training is finished
2026-10-30T07:54:10Z INFO     [CPU0] Training is finished

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