deploy: 46df531

FAIR-Chem · Apr 17, 2024 · 2b11937 · 2b11937
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diff --git a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt
diff --git a/_downloads/819e10305ddd6839cd7da05935b17060/mass-inference.txt b/_downloads/819e10305ddd6839cd7da05935b17060/mass-inference.txt
@@ -1,17 +1,17 @@
-2024-04-16 21:46:24 (INFO): Project root: /home/runner/work/ocp/ocp
+2024-04-16 23:01:59 (INFO): Project root: /home/runner/work/ocp/ocp
 /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/cuda/amp/grad_scaler.py:126: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.
   warnings.warn(
-2024-04-16 21:46:26 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
-2024-04-16 21:46:26 (INFO): amp: true
+2024-04-16 23:02:01 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+2024-04-16 23:02:01 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-04-16-21-45-36
-  commit: a0090b0
+  checkpoint_dir: ./checkpoints/2024-04-16-23-02-24
+  commit: 46df531
   identifier: ''
-  logs_dir: ./logs/tensorboard/2024-04-16-21-45-36
+  logs_dir: ./logs/tensorboard/2024-04-16-23-02-24
   print_every: 10
-  results_dir: ./results/2024-04-16-21-45-36
+  results_dir: ./results/2024-04-16-23-02-24
   seed: 0
-  timestamp_id: 2024-04-16-21-45-36
+  timestamp_id: 2024-04-16-23-02-24
 dataset:
   a2g_args:
     r_energy: false
@@ -122,29 +122,29 @@ test_dataset:
 trainer: ocp
 val_dataset: null
 
-2024-04-16 21:46:26 (INFO): Loading dataset: ase_db
-2024-04-16 21:46:26 (INFO): rank: 0: Sampler created...
-2024-04-16 21:46:26 (INFO): Batch balancing is disabled for single GPU training.
-2024-04-16 21:46:26 (INFO): rank: 0: Sampler created...
-2024-04-16 21:46:26 (INFO): Batch balancing is disabled for single GPU training.
-2024-04-16 21:46:26 (INFO): Loading model: gemnet_t
-2024-04-16 21:46:28 (INFO): Loaded GemNetT with 31671825 parameters.
-2024-04-16 21:46:28 (WARNING): Model gradient logging to tensorboard not yet supported.
-2024-04-16 21:46:28 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gndt_oc22_all_s2ef.pt
-2024-04-16 21:46:28 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. 
-2024-04-16 21:46:28 (WARNING): Scale factor comment not found in model
-2024-04-16 21:46:28 (INFO): Predicting on test.
+2024-04-16 23:02:01 (INFO): Loading dataset: ase_db
+2024-04-16 23:02:01 (INFO): rank: 0: Sampler created...
+2024-04-16 23:02:01 (INFO): Batch balancing is disabled for single GPU training.
+2024-04-16 23:02:01 (INFO): rank: 0: Sampler created...
+2024-04-16 23:02:01 (INFO): Batch balancing is disabled for single GPU training.
+2024-04-16 23:02:01 (INFO): Loading model: gemnet_t
+2024-04-16 23:02:03 (INFO): Loaded GemNetT with 31671825 parameters.
+2024-04-16 23:02:03 (WARNING): Model gradient logging to tensorboard not yet supported.
+2024-04-16 23:02:03 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gndt_oc22_all_s2ef.pt
+2024-04-16 23:02:03 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. 
+2024-04-16 23:02:03 (WARNING): Scale factor comment not found in model
+2024-04-16 23:02:03 (INFO): Predicting on test.
 device 0:   0%|                                           | 0/3 [00:00<?, ?it/s]/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
   storage = elem.storage()._new_shared(numel)
 /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
   storage = elem.storage()._new_shared(numel)
 /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/amp/autocast_mode.py:250: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
   warnings.warn(
-device 0:  33%|███████████▋                       | 1/3 [00:02<00:05,  2.99s/it]device 0:  67%|███████████████████████▎           | 2/3 [00:05<00:02,  2.88s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:07<00:00,  2.39s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:07<00:00,  2.54s/it]
+device 0:  33%|███████████▋                       | 1/3 [00:04<00:08,  4.11s/it]device 0:  67%|███████████████████████▎           | 2/3 [00:08<00:04,  4.25s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:09<00:00,  2.93s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:09<00:00,  3.28s/it]
 /home/runner/work/ocp/ocp/ocpmodels/trainers/ocp_trainer.py:510: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
   predictions[key] = np.array(predictions[key])
 /home/runner/work/ocp/ocp/ocpmodels/trainers/base_trainer.py:840: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
   np.array(gather_results[k])[idx]
-2024-04-16 21:46:36 (INFO): Writing results to ./results/2024-04-16-21-45-36/ocp_predictions.npz
-2024-04-16 21:46:36 (INFO): Total time taken: 7.780270338058472
-Elapsed time = 14.1 seconds
+2024-04-16 23:02:13 (INFO): Writing results to ./results/2024-04-16-23-02-24/ocp_predictions.npz
+2024-04-16 23:02:13 (INFO): Total time taken: 10.010130405426025
+Elapsed time = 16.4 seconds

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diff --git a/autoapi/index.html b/autoapi/index.html
@@ -179,6 +179,7 @@
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+<li class="toctree-l1"><a class="reference internal" href="../core/intro_series.html">Why model atoms for climate?</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../core/intro_series.html">Why model atoms for climate?</a></li>
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diff --git a/autoapi/ocpmodels/common/utils/index.html b/autoapi/ocpmodels/common/utils/index.html
@@ -179,6 +179,7 @@
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+<li class="toctree-l1"><a class="reference internal" href="../../../../core/intro_series.html">Why model atoms for climate?</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../core/install.html">Installation</a></li>
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diff --git a/autoapi/ocpmodels/datasets/_utils/index.html b/autoapi/ocpmodels/datasets/_utils/index.html
@@ -179,6 +179,7 @@
         </ul>
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 <ul class="nav bd-sidenav">
+<li class="toctree-l1"><a class="reference internal" href="../../../../core/intro_series.html">Why model atoms for climate?</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../core/install.html">Installation</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../core/quickstart.html">Using pre-trained models in ASE</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../core/gotchas.html">Common gotchas with OCP</a></li>