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

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000940000 1000410000 4096 Oct 23 03:57 .
drwxrwsrwx. 4         99 1000410000 4096 Oct 23 03:57 ..
drwxr-sr-x. 3 1000940000 1000410000 4096 Oct 23 03:57 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1023 03:57:38.751000 3 torch/distributed/run.py:874] 
W1023 03:57:38.751000 3 torch/distributed/run.py:874] *****************************************
W1023 03:57:38.751000 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 03:57:38.751000 3 torch/distributed/run.py:874] *****************************************
2026-10-23T03:57:43Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-10-23T03:57:43Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-10-23T03:57:44Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-23T03:57:44Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-23T03:57:44Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.298321
2026-10-23T03:57:45Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 2.570453
2026-10-23T03:57:46Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 2.022335
2026-10-23T03:57:47Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 1.155850
2026-10-23T03:57:48Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 0.756873
2026-10-23T03:57:50Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 0.701240
2026-10-23T03:57:51Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 0.502523
2026-10-23T03:57:52Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.512382
2026-10-23T03:57:53Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.625158
2026-10-23T03:57:54Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.599957
2026-10-23T03:57:56Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.498888
2026-10-23T03:57:57Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.460693
2026-10-23T03:57:58Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.405489
2026-10-23T03:57:59Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.393745
2026-10-23T03:58:00Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.657571
2026-10-23T03:58:02Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.695218
2026-10-23T03:58:03Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.298647
2026-10-23T03:58:04Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.369493
2026-10-23T03:58:05Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.584455
2026-10-23T03:58:06Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.491366
2026-10-23T03:58:07Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.466633
2026-10-23T03:58:09Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.570983
2026-10-23T03:58:10Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.644251
2026-10-23T03:58:11Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.125938
2026-10-23T03:58:11Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 0.707862 | Batches: 235
2026-10-23T03:58:11Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.701598 | Batches: 235
2026-10-23T03:58:11Z INFO     [CPU1] Training is finished
2026-10-23T03:58:11Z INFO     [CPU0] Training is finished

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