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

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000830000 1000430000 4096 Oct 30 14:46 .
drwxrwsrwx. 4         99 1000430000 4096 Oct 30 14:46 ..
drwxr-sr-x. 3 1000830000 1000430000 4096 Oct 30 14:46 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1030 14:46:30.073000 3 torch/distributed/run.py:851] 
W1030 14:46:30.073000 3 torch/distributed/run.py:851] *****************************************
W1030 14:46:30.073000 3 torch/distributed/run.py:851] 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 14:46:30.073000 3 torch/distributed/run.py:851] *****************************************
2026-10-30T14:47:40Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-10-30T14:47:40Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-10-30T14:47:40Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T14:47:40Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T14:47:40Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.296978
2026-10-30T14:47:41Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 1.388962
2026-10-30T14:47:42Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 1.374347
2026-10-30T14:47:44Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 1.329771
2026-10-30T14:47:45Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 0.637878
2026-10-30T14:47:46Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 0.625080
2026-10-30T14:47:48Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 0.489914
2026-10-30T14:47:49Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.515901
2026-10-30T14:47:50Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.523096
2026-10-30T14:47:52Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.604720
2026-10-30T14:47:53Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.404951
2026-10-30T14:47:54Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.471952
2026-10-30T14:47:55Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.365610
2026-10-30T14:47:57Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.376159
2026-10-30T14:47:58Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.650178
2026-10-30T14:47:59Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.638406
2026-10-30T14:48:00Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.291915
2026-10-30T14:48:02Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.375940
2026-10-30T14:48:03Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.620373
2026-10-30T14:48:04Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.522978
2026-10-30T14:48:06Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.549002
2026-10-30T14:48:07Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.533750
2026-10-30T14:48:08Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.637759
2026-10-30T14:48:09Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.170372
2026-10-30T14:48:10Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.659868 | Batches: 235
2026-10-30T14:48:10Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 0.670951 | Batches: 235
2026-10-30T14:48:10Z INFO     [CPU1] Training is finished
2026-10-30T14:48:10Z INFO     [CPU0] Training is finished

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