diffusion/train_g0.1_e100.log

Using bfloat16 Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
💡 Tip: For seamless cloud logging and experiment tracking, try installing [litlogger](https://pypi.org/project/litlogger/) to enable LitLogger, which logs metrics and artifacts automatically to the Lightning Experiments platform.
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [GPU-ec0c411a-ec4f-2dfd-997e-f5993509c181]
/work/gw97/w97000/envs/nenv2/lib/python3.12/site-packages/pytorch_lightning/utilities/model_summary/model_summary.py:242: Precision bf16-mixed is not supported by the model summary.  Estimated model size in MB will not be accurate. Using 32 bits instead.

  | Name        | Type            | Params | Mode  | FLOPs
----------------------------------------------------------------
0 | score_model | OptimizedModule | 2.6 M  | train | 0    
----------------------------------------------------------------
2.6 M     Trainable params
128       Non-trainable params
2.6 M     Total params
10.562    Total estimated model params size (MB)
152       Modules in train mode
0         Modules in eval mode
0         Total Flops
/work/gw97/w97000/envs/nenv2/lib/python3.12/site-packages/pytorch_lightning/utilities/_pytree.py:21: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.
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[rank: 0] Received SIGTERM: 15
Field data loaded to cuda:0 (0.10 GB, shape=(100000, 1, 16, 16))
Using NCSNpp2D (NCSN++ style, periodic BC)
Normalization range: [-1.2395, 1.2552]
EMA starts at epoch: 0
Output directory: runs/yukawa_L16_g0.1_ncsnpp/
Log-scale checkpoints (54 total): [1, 2, 3, 4, 5] ... [83, 86, 91, 95, 100]
Field data loaded to cuda:0 (0.10 GB, shape=(100000, 1, 16, 16))