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

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000940000 1000420000 4096 Oct 30 16:12 .
drwxrwsrwx. 4         99 1000420000 4096 Oct 30 16:12 ..
drwxr-sr-x. 3 1000940000 1000420000 4096 Oct 30 16:12 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1030 16:13:03.978000 3 torch/distributed/run.py:874] 
W1030 16:13:03.978000 3 torch/distributed/run.py:874] *****************************************
W1030 16:13:03.978000 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 16:13:03.978000 3 torch/distributed/run.py:874] *****************************************
2026-10-30T16:14:08Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-10-30T16:14:08Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-10-30T16:14:08Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T16:14:08Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-10-30T16:14:08Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.315990
2026-10-30T16:14:10Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 3.697366
2026-10-30T16:14:11Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 2.028656
2026-10-30T16:14:13Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 1.443664
2026-10-30T16:14:14Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 1.110456
2026-10-30T16:14:16Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 0.740094
2026-10-30T16:14:17Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 0.539824
2026-10-30T16:14:18Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.542397
2026-10-30T16:14:20Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.600806
2026-10-30T16:14:21Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.553880
2026-10-30T16:14:23Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.468592
2026-10-30T16:14:24Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.449088
2026-10-30T16:14:26Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.413276
2026-10-30T16:14:27Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.350596
2026-10-30T16:14:28Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.740428
2026-10-30T16:14:30Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.713654
2026-10-30T16:14:31Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.305694
2026-10-30T16:14:33Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.400738
2026-10-30T16:14:34Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.536530
2026-10-30T16:14:36Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.456930
2026-10-30T16:14:37Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.466254
2026-10-30T16:14:38Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.439263
2026-10-30T16:14:40Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.514140
2026-10-30T16:14:41Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.175442
2026-10-30T16:14:42Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 0.727941 | Batches: 235
2026-10-30T16:14:42Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.718074 | Batches: 235
2026-10-30T16:14:42Z INFO     [CPU0] Training is finished
2026-10-30T16:14:42Z INFO     [CPU1] Training is finished

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