diff --git a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt index 502220837..c7de0dfca 100644 --- a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt +++ b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt @@ -1,16 +1,16 @@ -2024-07-09 14:11:39 (INFO): Running in non-distributed local mode -2024-07-09 14:11:39 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem -2024-07-09 14:11:40 (INFO): amp: true +2024-07-10 16:28:36 (INFO): Running in non-distributed local mode +2024-07-10 16:28:36 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem +2024-07-10 16:28:37 (INFO): amp: true cmd: - checkpoint_dir: fine-tuning/checkpoints/2024-07-09-14-11-12-ft-oxides - commit: bf2b26e + checkpoint_dir: fine-tuning/checkpoints/2024-07-10-16-27-44-ft-oxides + commit: 36a17ad identifier: ft-oxides - logs_dir: fine-tuning/logs/tensorboard/2024-07-09-14-11-12-ft-oxides + logs_dir: fine-tuning/logs/tensorboard/2024-07-10-16-27-44-ft-oxides print_every: 10 - results_dir: fine-tuning/results/2024-07-09-14-11-12-ft-oxides + results_dir: fine-tuning/results/2024-07-10-16-27-44-ft-oxides seed: 0 - timestamp_id: 2024-07-09-14-11-12-ft-oxides - version: 0.1.dev1+gbf2b26e + timestamp_id: 2024-07-10-16-27-44-ft-oxides + version: 0.1.dev1+g36a17ad dataset: a2g_args: r_energy: true @@ -141,83 +141,83 @@ val_dataset: format: ase_db src: val.db -2024-07-09 14:11:40 (INFO): Loading dataset: ase_db -2024-07-09 14:11:40 (INFO): rank: 0: Sampler created... -2024-07-09 14:11:40 (INFO): Batch balancing is disabled for single GPU training. -2024-07-09 14:11:40 (INFO): rank: 0: Sampler created... -2024-07-09 14:11:40 (INFO): Batch balancing is disabled for single GPU training. -2024-07-09 14:11:40 (INFO): rank: 0: Sampler created... -2024-07-09 14:11:40 (INFO): Batch balancing is disabled for single GPU training. -2024-07-09 14:11:40 (INFO): Loading model: gemnet_oc -2024-07-09 14:11:40 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization'] -2024-07-09 14:11:43 (INFO): Loaded GemNetOC with 38864438 parameters. -2024-07-09 14:11:43 (WARNING): log_summary for Tensorboard not supported -2024-07-09 14:11:43 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated. -2024-07-09 14:11:43 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gnoc_oc22_oc20_all_s2ef.pt -2024-07-09 14:11:43 (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. +2024-07-10 16:28:37 (INFO): Loading dataset: ase_db +2024-07-10 16:28:37 (INFO): rank: 0: Sampler created... +2024-07-10 16:28:37 (INFO): Batch balancing is disabled for single GPU training. +2024-07-10 16:28:37 (INFO): rank: 0: Sampler created... +2024-07-10 16:28:37 (INFO): Batch balancing is disabled for single GPU training. +2024-07-10 16:28:37 (INFO): rank: 0: Sampler created... +2024-07-10 16:28:37 (INFO): Batch balancing is disabled for single GPU training. +2024-07-10 16:28:37 (INFO): Loading model: gemnet_oc +2024-07-10 16:28:37 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization'] +2024-07-10 16:28:39 (INFO): Loaded GemNetOC with 38864438 parameters. +2024-07-10 16:28:39 (WARNING): log_summary for Tensorboard not supported +2024-07-10 16:28:39 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated. +2024-07-10 16:28:40 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gnoc_oc22_oc20_all_s2ef.pt +2024-07-10 16:28:40 (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. /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) -2024-07-09 14:12:06 (INFO): energy_mae: 6.77e+00, forcesx_mae: 4.11e-02, forcesy_mae: 3.63e-02, forcesz_mae: 5.26e-02, forces_mae: 4.33e-02, forces_cosine_similarity: 8.24e-02, forces_magnitude_error: 7.42e-02, energy_forces_within_threshold: 0.00e+00, loss: 6.86e+00, lr: 5.00e-04, epoch: 1.69e-01, step: 1.00e+01 -2024-07-09 14:12:07 (INFO): Evaluating on val. +2024-07-10 16:29:02 (INFO): energy_mae: 6.77e+00, forcesx_mae: 4.11e-02, forcesy_mae: 3.63e-02, forcesz_mae: 5.26e-02, forces_mae: 4.33e-02, forces_cosine_similarity: 8.24e-02, forces_magnitude_error: 7.42e-02, energy_forces_within_threshold: 0.00e+00, loss: 6.86e+00, lr: 5.00e-04, epoch: 1.69e-01, step: 1.00e+01 +2024-07-10 16:29:03 (INFO): Evaluating on val. device 0: 0%| | 0/2 [00:00Fine tuning a model -
Elapsed time 67.7 seconds.
+
Elapsed time 68.0 seconds.
 

 

 ../../_images/e09235df67f6a4f604e2dc396140b3979de3a415db6696093790df3189ca2edf.png
@@ -906,7 +906,7 @@ 
Fine tuning the checkpoint
-
/tmp/ipykernel_2423/1448814737.py:12: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2290/1448814737.py:12: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

@@ -1199,7 +1199,7 @@ 
Running the training jobHide code cell output
 
 

-
Elapsed time = 206.6 seconds
+
Elapsed time = 207.0 seconds
 

 

 

@@ -1215,7 +1215,7 @@ 
Running the training job
-
'fine-tuning/checkpoints/2024-07-09-14-11-12-ft-oxides'
+
'fine-tuning/checkpoints/2024-07-10-16-27-44-ft-oxides'
 

 

 

@@ -1274,7 +1274,7 @@ 
Running the training job
-../../_images/ec3d78c828a48f27837aed2db2ea620c401fa3cc7fec032fead69ca09d84fb29.png
+../../_images/5619bffc5cbf78888b670444701903eb7a06f1d9b467bceef578151bc4f956c6.png
 

 

 

@@ -1285,7 +1285,7 @@ 
Running the training job
-
New MAE = 0.324 eV/atom
+
New MAE = 0.235 eV/atom
 

 

 

@@ -1304,7 +1304,7 @@ 
Running the training job
-../../_images/1bd3f6f137572394f45b2bea46d8a5d05c74e922aca09434f2a962c660c36a98.png
+../../_images/336759a1dc6295bc0edbf0a0fb8b76b26c6259d18205582f40cff7f41c093c24.png
 

 

 
It is possible to continue refining the fit. The simple things to do are to use more epochs of training. Eventually the MAE will stabilize, and then it may be necessary to adjust other optimization parameters like the learning rate (usually you decrease it).

diff --git a/core/gotchas.html b/core/gotchas.html
index 6f0e44060..98d820224 100644
--- a/core/gotchas.html
+++ b/core/gotchas.html
@@ -731,12 +731,12 @@ 
I want the energy of a gas phase atom    544         '{} not present in this ' 'calculation'.format(name)
     545     )
 
-File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:237, in OCPCalculator.calculate(self, atoms, properties, system_changes)
-    234 data_object = self.a2g.convert(atoms)
-    235 batch = data_list_collater([data_object], otf_graph=True)
---> 237 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
-    239 for key in predictions:
-    240     _pred = predictions[key]
+File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:235, in OCPCalculator.calculate(self, atoms, properties, system_changes)
+    232 data_object = self.a2g.convert(atoms)
+    233 batch = data_list_collater([data_object], otf_graph=True)
+--> 235 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
+    237 for key in predictions:
+    238     _pred = predictions[key]
 
 File /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/utils/_contextlib.py:115, in context_decorator.<locals>.decorate_context(*args, **kwargs)
     112 @functools.wraps(func)
@@ -922,7 +922,7 @@ 
I get wildly different energies from the different models
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2697/1677958285.py:11: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/1677958285.py:11: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

@@ -959,7 +959,7 @@ 
I get wildly different energies from the different models
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2697/2284884232.py:9: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/2284884232.py:9: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

@@ -988,11 +988,11 @@ 
I get wildly different energies from the different models
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2697/898007276.py:7: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/898007276.py:7: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

-
1.6709036827087402
+
1.6888058185577393
 

 

 

@@ -1099,12 +1099,12 @@ 
You need at least four atoms for molecules with some models    544         '{} not present in this ' 'calculation'.format(name)
     545     )
 
-File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:237, in OCPCalculator.calculate(self, atoms, properties, system_changes)
-    234 data_object = self.a2g.convert(atoms)
-    235 batch = data_list_collater([data_object], otf_graph=True)
---> 237 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
-    239 for key in predictions:
-    240     _pred = predictions[key]
+File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:235, in OCPCalculator.calculate(self, atoms, properties, system_changes)
+    232 data_object = self.a2g.convert(atoms)
+    233 batch = data_list_collater([data_object], otf_graph=True)
+--> 235 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
+    237 for key in predictions:
+    238     _pred = predictions[key]
 
 File /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/utils/_contextlib.py:115, in context_decorator.<locals>.decorate_context(*args, **kwargs)
     112 @functools.wraps(func)
@@ -1309,12 +1309,12 @@ 
To tag or not?    544         '{} not present in this ' 'calculation'.format(name)
     545     )
 
-File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:237, in OCPCalculator.calculate(self, atoms, properties, system_changes)
-    234 data_object = self.a2g.convert(atoms)
-    235 batch = data_list_collater([data_object], otf_graph=True)
---> 237 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
-    239 for key in predictions:
-    240     _pred = predictions[key]
+File ~/work/fairchem/fairchem/src/fairchem/core/common/relaxation/ase_utils.py:235, in OCPCalculator.calculate(self, atoms, properties, system_changes)
+    232 data_object = self.a2g.convert(atoms)
+    233 batch = data_list_collater([data_object], otf_graph=True)
+--> 235 predictions = self.trainer.predict(batch, per_image=False, disable_tqdm=True)
+    237 for key in predictions:
+    238     _pred = predictions[key]
 
 File /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/utils/_contextlib.py:115, in context_decorator.<locals>.decorate_context(*args, **kwargs)
     112 @functools.wraps(func)
@@ -1457,7 +1457,7 @@ 
To tag or not?
-
/tmp/ipykernel_2697/3906293788.py:3: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/3906293788.py:3: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

@@ -1501,11 +1501,11 @@ 
To tag or not?
-
/tmp/ipykernel_2697/4094489779.py:3: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/4094489779.py:3: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

-
-0.4297373294830322
+
-0.4297369122505188
 

 

 

@@ -1552,21 +1552,21 @@ 
Stochastic simulation results
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2697/3095522216.py:11: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/3095522216.py:11: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

-
1.2139860391616821 1.6319050749442676e-06
-1.2139861583709717
-1.2139849662780762
-1.2139837741851807
-1.213989019393921
-1.213986873626709
-1.2139880657196045
+
1.2139862775802612 1.9376552365568983e-06
+1.2139883041381836
+1.2139859199523926
+1.2139892578125
 1.2139837741851807
+1.2139856815338135
+1.2139835357666016
+1.2139892578125
+1.2139854431152344
 1.2139861583709717
-1.2139866352081299
-1.2139849662780762
+1.2139854431152344
 

 

 

@@ -1604,11 +1604,11 @@ 
The forces don’t sum to zero
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2697/2981184886.py:11: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2561/2981184886.py:11: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

-
array([ 0.00848194,  0.01409447, -0.05882657], dtype=float32)
+
array([ 0.00848049,  0.0140971 , -0.05883038], dtype=float32)
 

 

 

@@ -1621,7 +1621,7 @@ 
The forces don’t sum to zero
-
array([ 1.3416866e-07,  7.9278834e-08, -1.1920929e-07], dtype=float32)
+
array([-1.5000114e-07,  7.9977326e-08,  0.0000000e+00], dtype=float32)
 

 

 

diff --git a/core/inference.html b/core/inference.html
index 7fccd881a..a9108b8bb 100644
--- a/core/inference.html
+++ b/core/inference.html
@@ -646,12 +646,12 @@ 
Fast batched inference
 

 

-
--2024-07-09 14:17:02--  https://figshare.com/ndownloader/files/11948267
+
--2024-07-10 16:33:49--  https://figshare.com/ndownloader/files/11948267
 Resolving figshare.com (figshare.com)... 
 

 

-
52.212.236.71, 34.251.213.12, 2a05:d018:1f4:d000:4856:ab6:5d9e:fe0e, ...
-Connecting to figshare.com (figshare.com)|52.212.236.71|:443... 
+
52.215.106.69, 52.212.236.71, 2a05:d018:1f4:d003:3dee:9eef:2e6:4a2b, ...
+Connecting to figshare.com (figshare.com)|52.215.106.69|:443... 
 

 

 
connected.
@@ -661,13 +661,10 @@ 
Fast batched inference

 

 
302 Found
-Location: https://s3-eu-west-1.amazonaws.com/pstorage-cmu-348901238291901/11948267/data.db?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAI266R7V6O36O5JUA/20240709/eu-west-1/s3/aws4_request&X-Amz-Date=20240709T141702Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=9994bf27457b7fdedb9b8a0dd3e1fad30d4b9d38fb5855ee72678db49831b765 [following]
---2024-07-09 14:17:02--  https://s3-eu-west-1.amazonaws.com/pstorage-cmu-348901238291901/11948267/data.db?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAI266R7V6O36O5JUA/20240709/eu-west-1/s3/aws4_request&X-Amz-Date=20240709T141702Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=9994bf27457b7fdedb9b8a0dd3e1fad30d4b9d38fb5855ee72678db49831b765
-Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 
-

-

-
52.218.46.88, 52.92.1.24, 52.218.60.227, ...
-Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.218.46.88|:443... 
+Location: https://s3-eu-west-1.amazonaws.com/pstorage-cmu-348901238291901/11948267/data.db?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAI266R7V6O36O5JUA/20240710/eu-west-1/s3/aws4_request&X-Amz-Date=20240710T163350Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=68a7ba32898abaeaf1242dae7185303908cff55cedeb4576e44d30011f62dd34 [following]
+--2024-07-10 16:33:50--  https://s3-eu-west-1.amazonaws.com/pstorage-cmu-348901238291901/11948267/data.db?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAI266R7V6O36O5JUA/20240710/eu-west-1/s3/aws4_request&X-Amz-Date=20240710T163350Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=68a7ba32898abaeaf1242dae7185303908cff55cedeb4576e44d30011f62dd34
+Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 52.218.98.147, 52.218.28.19, 52.92.32.104, ...
+Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.218.98.147|:443... 
 

 

 
connected.
@@ -684,39 +681,27 @@ 
Fast batched inference

 

-
data.db               0%[                    ]  58.38K   247KB/s               
-

-

-
data.db               0%[                    ] 169.38K   358KB/s               
-

-

-
data.db               1%[                    ] 636.38K   897KB/s               
+
data.db               0%[                    ] 160.38K   759KB/s               
 

 

-
data.db               6%[>                   ]   2.48M  2.61MB/s               
+
data.db               3%[                    ]   1.37M  3.23MB/s               
 

 

-
data.db              18%[==>                 ]   7.57M  6.39MB/s               
+
data.db              20%[===>                ]   8.48M  13.4MB/s               
 

 

-
data.db              32%[=====>              ]  13.32M  9.37MB/s               
+
data.db              41%[=======>            ]  17.21M  20.4MB/s               
 

 

-
data.db              46%[========>           ]  19.05M  11.5MB/s               
+
data.db              63%[===========>        ]  25.95M  24.6MB/s               
 

 

-
data.db              60%[===========>        ]  24.90M  13.1MB/s               
+
data.db              84%[===============>    ]  34.60M  27.2MB/s               
 

 

-
data.db              74%[=============>      ]  30.63M  14.3MB/s               
-

-

-
data.db              88%[================>   ]  36.33M  15.3MB/s               
-

-

-
data.db             100%[===================>]  41.13M  16.4MB/s    in 2.5s    
+
data.db             100%[===================>]  41.13M  29.0MB/s    in 1.4s    
 
-2024-07-09 14:17:05 (16.4 MB/s) - ‘data.db’ saved [43125760/43125760]
+2024-07-10 16:33:52 (29.0 MB/s) - ‘data.db’ saved [43125760/43125760]
 

 

 

@@ -758,29 +743,29 @@ 
Fast batched inference
 

 

-
id|age|user  |formula|calculator|  energy|natoms| fmax|pbc|  volume|charge|    mass
- 1| 0s|runner|Au37   |unknown   | -96.129|    37|0.159|TTT|5771.976| 0.000|7287.763
- 2| 0s|runner|Au28   |unknown   | -65.693|    28|3.139|TTT|5068.935| 0.000|5515.064
- 3| 0s|runner|Au29   |unknown   | -71.706|    29|0.288|TTT|5184.740| 0.000|5712.031
- 4| 0s|runner|Au8    |unknown   | -16.751|     8|0.281|TTT|2863.348| 0.000|1575.733
- 5| 0s|runner|Au16   |unknown   | -37.166|    16|0.131|TTT|3923.762| 0.000|3151.465
- 6| 0s|runner|Au4    |unknown   | -11.599|     4|1.869|TTT| 156.940| 0.000| 787.866
- 7| 0s|runner|Au10   |unknown   | -21.713|    10|0.701|TTT|4112.512| 0.000|1969.666
- 8| 0s|runner|Au4    |unknown   | -11.902|     4|0.302|TTT| 156.940| 0.000| 787.866
- 9| 0s|runner|Au36   |unknown   | -93.701|    36|0.067|TTT|5663.627| 0.000|7090.796
-10| 0s|runner|Au37   |unknown   | -92.625|    37|0.254|TTT|5771.976| 0.000|7287.763
-11| 0s|runner|Au2    |unknown   |  -0.473|     2|0.000|TTT| 208.559| 0.000| 393.933
-12| 0s|runner|Au29   |unknown   | -69.638|    29|0.554|TTT|5184.740| 0.000|5712.031
-13| 0s|runner|Au19   |unknown   | -46.081|    19|0.145|TTT|4101.856| 0.000|3742.365
-14| 0s|runner|Au14   |unknown   | -31.015|    14|0.418|TTT|3847.524| 0.000|2757.532
-15| 0s|runner|Au40   |unknown   |-103.328|    40|0.402|TTT|5868.580| 0.000|7878.663
-16| 0s|runner|Au11   |unknown   | -24.226|    11|0.079|TTT|3414.029| 0.000|2166.632
-17| 0s|runner|Au35   |unknown   | -90.988|    35|0.058|TTT|5504.869| 0.000|6893.830
-18| 0s|runner|Au18   |unknown   | -39.521|    18|0.900|TTT|4250.202| 0.000|3545.398
-19| 0s|runner|Au12   |unknown   | -27.037|    12|0.230|TTT|3571.095| 0.000|2363.599
-20| 0s|runner|Au41   |unknown   |-106.786|    41|0.272|TTT|6012.425| 0.000|8075.629
+
id|age|user  |formula|calculator|  energy|natoms| fmax|pbc|   volume|charge|     mass
+ 1| 0s|runner|Au52   |unknown   |-137.735|    52|0.199|TTT| 6744.510| 0.000|10242.262
+ 2| 0s|runner|Au10   |unknown   | -20.920|    10|0.721|TTT| 4112.512| 0.000| 1969.666
+ 3| 0s|runner|Au4    |unknown   | -12.096|     4|0.187|TTT|  143.096| 0.000|  787.866
+ 4| 0s|runner|Au5    |unknown   |  -9.207|     5|1.052|TTT| 2575.618| 0.000|  984.833
+ 5| 0s|runner|Au7    |unknown   | -13.236|     7|0.392|TTT| 3511.808| 0.000| 1378.766
+ 6| 0s|runner|Au119  |unknown   |-327.888|   119|0.621|TTT|12284.672| 0.000|23439.022
+ 7| 0s|runner|Au4    |unknown   | -11.527|     4|0.424|TTT|  156.940| 0.000|  787.866
+ 8| 0s|runner|Au12   |unknown   | -27.463|    12|0.151|TTT| 3066.950| 0.000| 2363.599
+ 9| 0s|runner|Au52   |unknown   |-137.905|    52|0.158|TTT| 6744.510| 0.000|10242.262
+10| 0s|runner|Au27   |unknown   | -67.450|    27|0.407|TTT| 4914.709| 0.000| 5318.097
+11| 0s|runner|Au4    |unknown   | -11.872|     4|0.574|TTT|  156.940| 0.000|  787.866
+12| 0s|runner|Au36   |unknown   | -93.692|    36|0.121|TTT| 5663.627| 0.000| 7090.796
+13| 0s|runner|Au45   |unknown   |-117.721|    45|0.155|TTT| 6185.400| 0.000| 8863.496
+14| 0s|runner|Au16   |unknown   | -35.355|    16|1.151|TTT| 3923.762| 0.000| 3151.465
+15| 0s|runner|Au48   |unknown   |-124.508|    48|0.377|TTT| 6440.631| 0.000| 9454.395
+16| 0s|runner|Au41   |unknown   |-103.140|    41|0.838|TTT| 6012.425| 0.000| 8075.629
+17| 0s|runner|Au13   |unknown   | -29.197|    13|0.109|TTT| 3635.026| 0.000| 2560.565
+18| 0s|runner|Au17   |unknown   | -39.838|    17|0.058|TTT| 4121.531| 0.000| 3348.432
+19| 0s|runner|Au28   |unknown   | -86.927|    28|0.019|TTT|  526.183| 0.000| 5515.064
+20| 0s|runner|Au16   |unknown   | -37.467|    16|0.323|TTT| 3923.762| 0.000| 3151.465
 Rows: 50 (showing first 20)
-Keys: NEB, bulk, calc_time, cluster, config, diffusion, ediff, ediffg, encut, factor, fermi, gga, group, image, kpt1, kpt2, kpt3, miller, neural_energy, reax_energy, strain, structure, surf, train_set, traj, vacuum, volume, xc
+Keys: NEB, bulk, calc_time, cluster, concentration, config, diffusion, ediff, ediffg, encut, fermi, gga, group, image, kpt1, kpt2, kpt3, lattice, miller, neural_energy, reax_energy, site, structure, surf, train_set, traj, type, vacuum, volume, xc
 

 

 

@@ -881,7 +866,7 @@ 
Fast batched inference
 

 

-
2024-07-09 14:17:28 (INFO): Total time taken: 6.688116550445557
+
2024-07-10 16:34:13 (INFO): Total time taken: 8.430647373199463
 

 

 

@@ -950,7 +935,7 @@ 
Fast batched inference
 

 

-../_images/20119ebabd48f33476c0d005b06b2a0dd7a215cc88c5f66182ccd469bcff0e8a.png
+../_images/6a1d6b0df93617c90cb3eff7991ca38c17638566984c00e87abd508f9ee2ce4a.png
 

 

 
@@ -999,104 +984,101 @@ 
The ASE calculator way
0it [00:00, ?it/s]
 

 

-
/tmp/ipykernel_2741/402181013.py:7: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2603/402181013.py:7: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

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+
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-
Elapsed time 7e+00 seconds
+
Elapsed time 9e+00 seconds
 

 

 

@@ -1114,7 +1096,7 @@ 
The ASE calculator way
 

 

-../_images/d8f000c5866310197f993a7572f8fecc25292a36dab7b71d7508e7eec2cc2434.png
+../_images/86c6c30bcba70e4dc7045ed905b57d667d70fd06a61b46a3a2001c30c1b632ec.png
 

 

 
@@ -1130,7 +1112,7 @@ 
Comparing ASE calculator and main.py
-
52.66483077912157
+
62.14755616196559
 

 

 

@@ -1142,7 +1124,7 @@ 
Comparing ASE calculator and main.py
-
(-236.94300270080566, 236.9430046081543)
+
(-328.9178466796875, 328.9178466796875)
 

 

 

@@ -1154,7 +1136,7 @@ 
Comparing ASE calculator and main.py
-../_images/deabea6d50267eb0199707fd11c4215082556e20ab5e2e17344d1dde87586a2e.png
+../_images/737b5c27afd393eda611180faa0e6913cf2913d35de9ee976ce8393895b088f2.png
 

 

 
Here we see many of the differences are very small. 0.0078125 = 1 / 128, and these errors strongly suggest some kind of mixed precision is responsible for these differences. It is an open issue to remove them and identify where the cause is.

@@ -1165,19 +1147,19 @@ 
Comparing ASE calculator and main.py
-
array([[ 0.00000000e+00, -3.04521866e+01, -2.49373627e+01, ...,
-        -3.49432831e+01, -8.12342224e+01, -6.72080231e+01],
-       [ 3.04521866e+01,  0.00000000e+00,  5.51482391e+00, ...,
-        -4.49109650e+00, -5.07820358e+01, -3.67558365e+01],
-       [ 2.49373627e+01, -5.51482391e+00,  0.00000000e+00, ...,
-        -1.00059204e+01, -5.62968597e+01, -4.22706604e+01],
+
array([[   0.        , -123.06163406, -131.50551605, ..., -127.80545235,
+         -95.427742  ,  -58.97216797],
+       [ 123.06163406,    0.        ,   -8.44388199, ...,   -4.74381828,
+          27.63389206,   64.08946609],
+       [ 131.50551605,    8.44388199,    0.        , ...,    3.70006371,
+          36.07777405,   72.53334808],
        ...,
-       [ 3.49432831e+01,  4.49109650e+00,  1.00059204e+01, ...,
-         0.00000000e+00, -4.62909393e+01, -3.22647400e+01],
-       [ 8.12342224e+01,  5.07820358e+01,  5.62968597e+01, ...,
-         4.62909393e+01,  0.00000000e+00,  1.40261993e+01],
-       [ 6.72080154e+01,  3.67558289e+01,  4.22706528e+01, ...,
-         3.22647324e+01, -1.40262070e+01, -7.62939453e-06]])
+       [ 127.80545235,    4.74381828,   -3.70006371, ...,    0.        ,
+          32.37771034,   68.83328438],
+       [  95.427742  ,  -27.63389206,  -36.07777405, ...,  -32.37771034,
+           0.        ,   36.45557404],
+       [  58.97216797,  -64.08946609,  -72.53334808, ...,  -68.83328438,
+         -36.45557404,    0.        ]])
 

 

 

diff --git a/core/lmdb_dataset_creation.html b/core/lmdb_dataset_creation.html
index d23cb3c6e..890f113b9 100644
--- a/core/lmdb_dataset_creation.html
+++ b/core/lmdb_dataset_creation.html
@@ -687,7 +687,7 @@ 
Generate toy dataset: Relaxation of CO on Cu
-
/tmp/ipykernel_2828/901556023.py:8: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2689/901556023.py:8: DeprecationWarning: Please use atoms.calc = calc
   adslab.set_calculator(EMT())
 

 

@@ -902,46 +902,49 @@ 
Structure to Energy and Forces (S2EF) LMDBs
  0%|          | 0/1001 [00:00<?, ?it/s]
 

 

-
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+
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diff --git a/core/ocpapi.html b/core/ocpapi.html
index 59ed19d24..e9e9205d8 100644
--- a/core/ocpapi.html
+++ b/core/ocpapi.html
@@ -664,7 +664,7 @@ 
Installation
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
 

 

-
fairchem-demo-ocpapi 0.1.dev1+gbf2b26e requires requests==2.32.0, but you have requests 2.31.0 which is incompatible.
+
fairchem-demo-ocpapi 0.1.dev1+g36a17ad requires requests==2.32.0, but you have requests 2.31.0 which is incompatible.
 

 

 
pymatgen 2024.6.10 requires requests>=2.32, but you have requests 2.31.0 which is incompatible.
diff --git a/core/quickstart.html b/core/quickstart.html
index 61418213d..d2a5c4bf3 100644
--- a/core/quickstart.html
+++ b/core/quickstart.html
@@ -701,60 +701,60 @@ 
Using pre-trained models in ASE
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

-
/tmp/ipykernel_2885/3462928393.py:13: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2745/3462928393.py:13: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:18:03     -110.398659        1.630680
+BFGS:    0 16:34:50     -110.398659        1.630680
 

 

-
BFGS:    1 14:18:03     -110.545036        0.925020
+
BFGS:    1 16:34:50     -110.545036        0.925020
 

 

-
BFGS:    2 14:18:03     -110.622719        0.562895
+
BFGS:    2 16:34:50     -110.622719        0.562895
 

 

-
BFGS:    3 14:18:04     -110.613007        0.583018
+
BFGS:    3 16:34:51     -110.613007        0.583018
 

 

-
BFGS:    4 14:18:04     -110.641937        0.461219
+
BFGS:    4 16:34:51     -110.641937        0.461219
 

 

-
BFGS:    5 14:18:05     -110.691620        0.362131
+
BFGS:    5 16:34:52     -110.691620        0.362131
 

 

-
BFGS:    6 14:18:05     -110.723862        0.592763
+
BFGS:    6 16:34:52     -110.723862        0.592763
 

 

-
BFGS:    7 14:18:05     -110.764206        0.712022
+
BFGS:    7 16:34:52     -110.764206        0.712022
 

 

-
BFGS:    8 14:18:06     -110.869545        0.522792
+
BFGS:    8 16:34:53     -110.869545        0.522792
 

 

-
BFGS:    9 14:18:06     -110.938713        0.170553
+
BFGS:    9 16:34:53     -110.938713        0.170553
 

 

-
BFGS:   10 14:18:07     -110.977699        0.083886
+
BFGS:   10 16:34:53     -110.977699        0.083886
 

 

-
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+
BFGS:   11 16:34:54     -110.992668        0.071652
 

 

-
BFGS:   12 14:18:07     -110.999657        0.061177
+
BFGS:   12 16:34:54     -110.999657        0.061177
 

 

-
BFGS:   13 14:18:08     -110.995178        0.059450
+
BFGS:   13 16:34:55     -110.995178        0.059450
 

 

-
BFGS:   14 14:18:08     -111.005981        0.060318
+
BFGS:   14 16:34:55     -111.005981        0.060318
 

 

-
BFGS:   15 14:18:08     -111.007721        0.062097
+
BFGS:   15 16:34:55     -111.007721        0.062097
 

 

-
BFGS:   16 14:18:09     -111.010895        0.035077
+
BFGS:   16 16:34:56     -111.010895        0.035077
 

 

 ../_images/ea7ac8e20e191a15de6e417770d86a627492010be04a5f6c56083ee6b1ac9289.png
diff --git a/execution_time.html b/execution_time.html
index d17635c94..e2728725c 100644
--- a/execution_time.html
+++ b/execution_time.html
@@ -634,99 +634,99 @@ 
Notebook execution times
core/fine-tuning/fine-tuning-oxides

-
2024-07-09 14:16

+
2024-07-10 16:33

 
auto

-
367.49

+
367.15

 
✅

 
 
core/gotchas

-
2024-07-09 14:17

+
2024-07-10 16:33

 
auto

-
44.38

+
33.37

 
✅

 
 
core/inference

-
2024-07-09 14:17

+
2024-07-10 16:34

 
auto

-
39.7

+
37.74

 
✅

 
 
core/lmdb_dataset_creation

-
2024-07-09 14:17

+
2024-07-10 16:34

 
auto

-
11.17

+
11.64

 
✅

 
 
core/ocpapi

-
2024-07-09 14:17

+
2024-07-10 16:34

 
auto

-
3.45

+
3.62

 
✅

 
 
core/quickstart

-
2024-07-09 14:18

+
2024-07-10 16:34

 
auto

-
15.12

+
15.51

 
✅

 
 
legacy_tutorials/OCP_Tutorial

-
2024-07-09 14:32

+
2024-07-10 16:49

 
auto

-
845.31

+
846.18

 
✅

 
 
legacy_tutorials/data_preprocessing

-
2024-07-09 14:32

+
2024-07-10 16:49

 
auto

-
11.67

+
10.69

 
✅

 
 
legacy_tutorials/data_visualization

-
2024-07-09 14:33

+
2024-07-10 16:50

 
auto

-
44.61

+
47.02

 
✅

 
 
tutorials/NRR/NRR_example

-
2024-07-09 14:46

+
2024-07-10 17:01

 
auto

-
785.3

+
694.28

 
✅

 
 
tutorials/OCP-introduction

-
2024-07-09 14:50

+
2024-07-10 17:05

 
auto

-
243.0

+
245.63

 
✅

 
 
tutorials/adsorbml_walkthrough

-
2024-07-09 14:57

+
2024-07-10 17:14

 
auto

-
448.01

+
502.2

 
✅

 
 
tutorials/advanced/embeddings

-
2024-07-09 14:59

+
2024-07-10 17:15

 
auto

-
86.58

+
87.55

 
✅

 
 
tutorials/advanced/fine-tuning-in-python

-
2024-07-09 15:02

+
2024-07-10 17:19

 
auto

-
210.32

+
213.4

 
✅

 
 
tutorials/cattsunami_walkthrough

-
2024-07-09 15:02

+
2024-07-10 17:19

 
auto

-
0.71

+
0.77

 
✅

 
 
tutorials/intro

-
2024-07-09 15:02

+
2024-07-10 17:19

 
auto

-
4.11

+
4.35

 
✅

 
 
diff --git a/legacy_tutorials/OCP_Tutorial.html b/legacy_tutorials/OCP_Tutorial.html
index 1accf3d54..e5b791977 100644
--- a/legacy_tutorials/OCP_Tutorial.html
+++ b/legacy_tutorials/OCP_Tutorial.html
@@ -1041,311 +1041,311 @@ 
Structural relaxations
 

 
       Step     Time          Energy          fmax
-LBFGS:    0 14:18:14       15.804700        6.776430
+LBFGS:    0 16:35:01       15.804700        6.776430
 

 

-
LBFGS:    1 14:18:14       12.190607        4.323222
+
LBFGS:    1 16:35:01       12.190607        4.323222
 

 

-
LBFGS:    2 14:18:14       10.240169        2.265527
+
LBFGS:    2 16:35:01       10.240169        2.265527
 

 

-
LBFGS:    3 14:18:14        9.779223        0.937247
+
LBFGS:    3 16:35:02        9.779223        0.937247
 

 

-
LBFGS:    4 14:18:14        9.671525        0.770173
+
LBFGS:    4 16:35:02        9.671525        0.770173
 

 

-
LBFGS:    5 14:18:14        9.574461        0.663540
+
LBFGS:    5 16:35:02        9.574461        0.663540
 

 

-
LBFGS:    6 14:18:14        9.537502        0.571800
+
LBFGS:    6 16:35:02        9.537502        0.571800
 

 

-
LBFGS:    7 14:18:14        9.516673        0.446620
+
LBFGS:    7 16:35:02        9.516673        0.446620
 

 

-
LBFGS:    8 14:18:14        9.481330        0.461143
+
LBFGS:    8 16:35:02        9.481330        0.461143
 

 

-
LBFGS:    9 14:18:14        9.462255        0.293081
+
LBFGS:    9 16:35:02        9.462255        0.293081
 

 

-
LBFGS:   10 14:18:14        9.448937        0.249010
+
LBFGS:   10 16:35:02        9.448937        0.249010
 

 

-
LBFGS:   11 14:18:14        9.433813        0.237051
+
LBFGS:   11 16:35:02        9.433813        0.237051
 

 

-
LBFGS:   12 14:18:14        9.418884        0.260245
+
LBFGS:   12 16:35:02        9.418884        0.260245
 

 

-
LBFGS:   13 14:18:14        9.409649        0.253162
+
LBFGS:   13 16:35:02        9.409649        0.253162
 

 

-
LBFGS:   14 14:18:14        9.404838        0.162398
+
LBFGS:   14 16:35:02        9.404838        0.162398
 

 

-
LBFGS:   15 14:18:14        9.401753        0.182298
+
LBFGS:   15 16:35:02        9.401753        0.182298
 

 

-
LBFGS:   16 14:18:14        9.397314        0.259163
+
LBFGS:   16 16:35:02        9.397314        0.259163
 

 

-
/tmp/ipykernel_2916/747130225.py:23: DeprecationWarning: Please use atoms.calc = calc
-  adslab.set_calculator(EMT())
+
LBFGS:   17 16:35:02        9.387947        0.345022
 

 

-
LBFGS:   17 14:18:14        9.387947        0.345022
+
/tmp/ipykernel_2777/747130225.py:23: DeprecationWarning: Please use atoms.calc = calc
+  adslab.set_calculator(EMT())
 

 

-
LBFGS:   18 14:18:14        9.370825        0.407041
+
LBFGS:   18 16:35:02        9.370825        0.407041
 

 

-
LBFGS:   19 14:18:14        9.342222        0.433340
+
LBFGS:   19 16:35:02        9.342222        0.433340
 

 

-
LBFGS:   20 14:18:14        9.286822        0.500200
+
LBFGS:   20 16:35:02        9.286822        0.500200
 

 

-
LBFGS:   21 14:18:14        9.249910        0.524052
+
LBFGS:   21 16:35:02        9.249910        0.524052
 

 

-
LBFGS:   22 14:18:14        9.187179        0.511994
+
LBFGS:   22 16:35:02        9.187179        0.511994
 

 

-
LBFGS:   23 14:18:14        9.124811        0.571796
+
LBFGS:   23 16:35:02        9.124811        0.571796
 

 

-
LBFGS:   24 14:18:15        9.066185        0.540934
+
LBFGS:   24 16:35:02        9.066185        0.540934
 

 

-
LBFGS:   25 14:18:15        9.000116        1.079833
+
LBFGS:   25 16:35:02        9.000116        1.079833
 

 

-
LBFGS:   26 14:18:15        8.893632        0.752759
+
LBFGS:   26 16:35:02        8.893632        0.752759
 

 

-
LBFGS:   27 14:18:15        8.845939        0.332051
+
LBFGS:   27 16:35:02        8.845939        0.332051
 

 

-
LBFGS:   28 14:18:15        8.815173        0.251242
+
LBFGS:   28 16:35:02        8.815173        0.251242
 

 

-
LBFGS:   29 14:18:15        8.808721        0.214337
+
LBFGS:   29 16:35:02        8.808721        0.214337
 

 

-
LBFGS:   30 14:18:15        8.794643        0.154611
+
LBFGS:   30 16:35:02        8.794643        0.154611
 

 

-
LBFGS:   31 14:18:15        8.789162        0.201404
+
LBFGS:   31 16:35:02        8.789162        0.201404
 

 

-
LBFGS:   32 14:18:15        8.782320        0.175517
+
LBFGS:   32 16:35:02        8.782320        0.175517
 

 

-
LBFGS:   33 14:18:15        8.780394        0.103718
+
LBFGS:   33 16:35:02        8.780394        0.103718
 

 

-
LBFGS:   34 14:18:15        8.778410        0.107611
+
LBFGS:   34 16:35:02        8.778410        0.107611
 

 

-
LBFGS:   35 14:18:15        8.775079        0.179747
+
LBFGS:   35 16:35:02        8.775079        0.179747
 

 

-
LBFGS:   36 14:18:15        8.766987        0.333401
+
LBFGS:   36 16:35:02        8.766987        0.333401
 

 

-
LBFGS:   37 14:18:15        8.750249        0.530715
+
LBFGS:   37 16:35:02        8.750249        0.530715
 

 

-
LBFGS:   38 14:18:15        8.725928        0.685116
+
LBFGS:   38 16:35:02        8.725928        0.685116
 

 

-
LBFGS:   39 14:18:15        8.702312        0.582260
+
LBFGS:   39 16:35:02        8.702312        0.582260
 

 

-
LBFGS:   40 14:18:15        8.661515        0.399625
+
LBFGS:   40 16:35:02        8.661515        0.399625
 

 

-
LBFGS:   41 14:18:15        8.643432        0.558474
+
LBFGS:   41 16:35:02        8.643432        0.558474
 

 

-
LBFGS:   42 14:18:15        8.621201        0.367288
+
LBFGS:   42 16:35:02        8.621201        0.367288
 

 

-
LBFGS:   43 14:18:15        8.614414        0.139424
+
LBFGS:   43 16:35:02        8.614414        0.139424
 

 

-
LBFGS:   44 14:18:15        8.610785        0.137160
+
LBFGS:   44 16:35:02        8.610785        0.137160
 

 

-
LBFGS:   45 14:18:15        8.608134        0.146375
+
LBFGS:   45 16:35:02        8.608134        0.146375
 

 

-
LBFGS:   46 14:18:15        8.604928        0.119648
+
LBFGS:   46 16:35:02        8.604928        0.119648
 

 

-
LBFGS:   47 14:18:15        8.599151        0.135424
+
LBFGS:   47 16:35:02        8.599151        0.135424
 

 

-
LBFGS:   48 14:18:15        8.594063        0.147913
+
LBFGS:   48 16:35:02        8.594063        0.147913
 

 

-
LBFGS:   49 14:18:15        8.589493        0.153840
+
LBFGS:   49 16:35:02        8.589493        0.153840
 

 

-
LBFGS:   50 14:18:15        8.587274        0.088460
+
LBFGS:   50 16:35:02        8.587274        0.088460
 

 

-
LBFGS:   51 14:18:15        8.584633        0.093750
+
LBFGS:   51 16:35:02        8.584633        0.093750
 

 

-
LBFGS:   52 14:18:15        8.580239        0.140870
+
LBFGS:   52 16:35:02        8.580239        0.140870
 

 

-
LBFGS:   53 14:18:15        8.572938        0.254272
+
LBFGS:   53 16:35:02        8.572938        0.254272
 

 

-
LBFGS:   54 14:18:15        8.563343        0.291885
+
LBFGS:   54 16:35:02        8.563343        0.291885
 

 

-
LBFGS:   55 14:18:15        8.554117        0.196557
+
LBFGS:   55 16:35:02        8.554117        0.196557
 

 

-
LBFGS:   56 14:18:15        8.547597        0.129064
+
LBFGS:   56 16:35:02        8.547597        0.129064
 

 

-
LBFGS:   57 14:18:15        8.542086        0.128020
+
LBFGS:   57 16:35:02        8.542086        0.128020
 

 

-
LBFGS:   58 14:18:15        8.535432        0.098202
+
LBFGS:   58 16:35:02        8.535432        0.098202
 

 

-
LBFGS:   59 14:18:15        8.533622        0.127672
+
LBFGS:   59 16:35:02        8.533622        0.127672
 

 

-
LBFGS:   60 14:18:15        8.527487        0.116729
+
LBFGS:   60 16:35:02        8.527487        0.116729
 

 

-
LBFGS:   61 14:18:15        8.523863        0.121762
+
LBFGS:   61 16:35:02        8.523863        0.121762
 

 

-
LBFGS:   62 14:18:15        8.519229        0.130541
+
LBFGS:   62 16:35:02        8.519229        0.130541
 

 

-
LBFGS:   63 14:18:15        8.515424        0.101902
+
LBFGS:   63 16:35:02        8.515424        0.101902
 

 

-
LBFGS:   64 14:18:15        8.511240        0.212223
+
LBFGS:   64 16:35:02        8.511240        0.212223
 

 

-
LBFGS:   65 14:18:15        8.507967        0.266593
+
LBFGS:   65 16:35:02        8.507967        0.266593
 

 

-
LBFGS:   66 14:18:15        8.503903        0.237734
+
LBFGS:   66 16:35:02        8.503903        0.237734
 

 

-
LBFGS:   67 14:18:15        8.497575        0.162253
+
LBFGS:   67 16:35:02        8.497575        0.162253
 

 

-
LBFGS:   68 14:18:15        8.485434        0.202203
+
LBFGS:   68 16:35:02        8.485434        0.202203
 

 

-
LBFGS:   69 14:18:15        8.466738        0.215895
+
LBFGS:   69 16:35:02        8.466738        0.215895
 

 

-
LBFGS:   70 14:18:15        8.467607        0.334764
+
LBFGS:   70 16:35:02        8.467607        0.334764
 

 

-
LBFGS:   71 14:18:15        8.454037        0.106310
+
LBFGS:   71 16:35:02        8.454037        0.106310
 

 

-
LBFGS:   72 14:18:15        8.448980        0.119721
+
LBFGS:   72 16:35:02        8.448980        0.119721
 

 

-
LBFGS:   73 14:18:15        8.446550        0.099221
+
LBFGS:   73 16:35:02        8.446550        0.099221
 

 

-
LBFGS:   74 14:18:15        8.444705        0.056244
+
LBFGS:   74 16:35:02        8.444705        0.056244
 

 

-
LBFGS:   75 14:18:15        8.443403        0.038831
+
LBFGS:   75 16:35:02        8.443403        0.038831
 

 

-
LBFGS:   76 14:18:15        8.442646        0.054772
+
LBFGS:   76 16:35:02        8.442646        0.054772
 

 

-
LBFGS:   77 14:18:15        8.442114        0.061370
+
LBFGS:   77 16:35:02        8.442114        0.061370
 

 

-
LBFGS:   78 14:18:15        8.440960        0.058800
+
LBFGS:   78 16:35:02        8.440960        0.058800
 

 

-
LBFGS:   79 14:18:15        8.439820        0.048198
+
LBFGS:   79 16:35:02        8.439820        0.048198
 

 

-
LBFGS:   80 14:18:15        8.438600        0.051251
+
LBFGS:   80 16:35:02        8.438600        0.051251
 

 

-
LBFGS:   81 14:18:15        8.437429        0.054130
+
LBFGS:   81 16:35:02        8.437429        0.054130
 

 

-
LBFGS:   82 14:18:15        8.435695        0.067234
+
LBFGS:   82 16:35:02        8.435695        0.067234
 

 

-
LBFGS:   83 14:18:15        8.431957        0.085678
+
LBFGS:   83 16:35:02        8.431957        0.085678
 

 

-
LBFGS:   84 14:18:15        8.423485        0.133240
+
LBFGS:   84 16:35:02        8.423485        0.133240
 

 

-
LBFGS:   85 14:18:15        8.413846        0.207812
+
LBFGS:   85 16:35:02        8.413846        0.207812
 

 

-
LBFGS:   86 14:18:15        8.404849        0.178747
+
LBFGS:   86 16:35:02        8.404849        0.178747
 

 

-
LBFGS:   87 14:18:15        8.385339        0.169017
+
LBFGS:   87 16:35:02        8.385339        0.169017
 

 

-
LBFGS:   88 14:18:15        8.386849        0.187645
+
LBFGS:   88 16:35:02        8.386849        0.187645
 

 

-
LBFGS:   89 14:18:15        8.371078        0.118124
+
LBFGS:   89 16:35:02        8.371078        0.118124
 

 

-
LBFGS:   90 14:18:15        8.368801        0.094222
+
LBFGS:   90 16:35:03        8.368801        0.094222
 

 

-
LBFGS:   91 14:18:15        8.366226        0.066960
+
LBFGS:   91 16:35:03        8.366226        0.066960
 

 

-
LBFGS:   92 14:18:15        8.361680        0.054964
+
LBFGS:   92 16:35:03        8.361680        0.054964
 

 

-
LBFGS:   93 14:18:15        8.360631        0.047342
+
LBFGS:   93 16:35:03        8.360631        0.047342
 

 

-
LBFGS:   94 14:18:15        8.359692        0.024179
+
LBFGS:   94 16:35:03        8.359692        0.024179
 

 

-
LBFGS:   95 14:18:15        8.359361        0.015549
+
LBFGS:   95 16:35:03        8.359361        0.015549
 

 

-
LBFGS:   96 14:18:15        8.359163        0.014284
+
LBFGS:   96 16:35:03        8.359163        0.014284
 

 

-
LBFGS:   97 14:18:15        8.359102        0.015615
+
LBFGS:   97 16:35:03        8.359102        0.015615
 

 

-
LBFGS:   98 14:18:15        8.359048        0.015492
+
LBFGS:   98 16:35:03        8.359048        0.015492
 

 

-
LBFGS:   99 14:18:15        8.358986        0.014214
+
LBFGS:   99 16:35:03        8.358986        0.014214
 

 

-
LBFGS:  100 14:18:15        8.358921        0.013159
+
LBFGS:  100 16:35:03        8.358921        0.013159
 

 

 
/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/ase/io/extxyz.py:311: UserWarning: Skipping unhashable information adsorbate_info
@@ -1613,7 +1613,7 @@ 
Adsorption energy
/tmp/ipykernel_2916/2478225434.py:7: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_2777/2478225434.py:7: DeprecationWarning: Please use atoms.calc = calc
   raw_slab.set_calculator(EMT())
 

 

@@ -1903,7 +1903,7 @@ 
Imports#<
 

 

 

-
2024-07-09 14:18:21 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem
+
2024-07-10 16:35:09 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem
 

 

 

@@ -1956,13 +1956,13 @@ 
Define the Config
-
--2024-07-09 14:18:22--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc-large.pt
+
--2024-07-10 16:35:09--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc-large.pt
 

 

-
Resolving github.com (github.com)... 140.82.113.4
+
Resolving github.com (github.com)... 140.82.113.3
 

 

-
Connecting to github.com (github.com)|140.82.113.4|:443... connected.
+
Connecting to github.com (github.com)|140.82.113.3|:443... connected.
 

 

 
HTTP request sent, awaiting response... 302 Found
@@ -1971,13 +1971,13 @@ 
Define the Config
Location: https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc-large.pt [following]
 

 

-
--2024-07-09 14:18:22--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc-large.pt
+
--2024-07-10 16:35:09--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc-large.pt
 

 

-
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...
+
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...
 

 

-
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.
+
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
 

 

 
HTTP request sent, awaiting response... 200 OK
@@ -1992,25 +1992,25 @@ 
Define the Config

 

 

-
     0K .......... .......... ......                          100% 11.8M=0.002s
+
     0K .......... .......... ......                          100% 33.3M=0.001s
 

 

 

 

 

-
2024-07-09 14:18:23 (11.8 MB/s) - ‘gemnet-oc-large.pt’ saved [27199/27199]
+
2024-07-10 16:35:09 (33.3 MB/s) - ‘gemnet-oc-large.pt’ saved [27199/27199]
 

 

 

 

 

-
--2024-07-09 14:18:23--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc.pt
+
--2024-07-10 16:35:09--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc.pt
 

 

-
Resolving github.com (github.com)... 140.82.113.4
+
Resolving github.com (github.com)... 140.82.113.3
 

 

-
Connecting to github.com (github.com)|140.82.113.4|:443... connected.
+
Connecting to github.com (github.com)|140.82.113.3|:443... connected.
 

 

 
HTTP request sent, awaiting response... 302 Found
@@ -2019,13 +2019,13 @@ 
Define the Config
Location: https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc.pt [following]
 

 

-
--2024-07-09 14:18:23--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc.pt
+
--2024-07-10 16:35:10--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-oc.pt
 

 

-
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.110.133, 185.199.108.133, ...
+
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.110.133, 185.199.108.133, ...
 

 

-
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.
+
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.
 

 

 
HTTP request sent, awaiting response... 200 OK
@@ -2040,25 +2040,25 @@ 
Define the Config

 

 

-
     0K .......... ......                                     100% 13.2M=0.001s
+
     0K .......... ......                                     100% 24.3M=0.001s
 

 

 

 

 

-
2024-07-09 14:18:23 (13.2 MB/s) - ‘gemnet-oc.pt’ saved [16963/16963]
+
2024-07-10 16:35:10 (24.3 MB/s) - ‘gemnet-oc.pt’ saved [16963/16963]
 

 

 

 

 

-
--2024-07-09 14:18:23--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-dT.json
+
--2024-07-10 16:35:10--  https://github.com/FAIR-Chem/fairchem/raw/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-dT.json
 

 

-
Resolving github.com (github.com)... 140.82.113.4
+
Resolving github.com (github.com)... 140.82.113.3
 

 

-
Connecting to github.com (github.com)|140.82.113.4|:443... connected.
+
Connecting to github.com (github.com)|140.82.113.3|:443... connected.
 

 

 
HTTP request sent, awaiting response... 302 Found
@@ -2067,13 +2067,13 @@ 
Define the Config
Location: https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-dT.json [following]
 

 

-
--2024-07-09 14:18:23--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-dT.json
+
--2024-07-10 16:35:10--  https://raw.githubusercontent.com/FAIR-Chem/fairchem/main/configs/s2ef/all/gemnet/scaling_factors/gemnet-dT.json
 

 

-
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.111.133, 185.199.109.133, ...
+
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.108.133, ...
 

 

-
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
+
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.
 

 

 
HTTP request sent, awaiting response... 200 OK
@@ -2088,13 +2088,13 @@ 
Define the Config

 

 

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     0K                                                       100% 46.5M=0s
+
     0K                                                       100% 44.6M=0s
 

 

 

 

 

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2024-07-09 14:18:24 (46.5 MB/s) - ‘gemnet-dT.json’ saved [816/816]
+
2024-07-10 16:35:10 (44.6 MB/s) - ‘gemnet-dT.json’ saved [816/816]
 

 

 

@@ -2236,20 +2236,20 @@ 
Create the trainer
-
2024-07-09 14:18:24 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:35:10 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:18:24 (INFO): amp: true
+
2024-07-10 16:35:10 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-17-36-S2EF-example
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-34-08-S2EF-example
+  commit: 36a17ad
   identifier: S2EF-example
-  logs_dir: ./logs/tensorboard/2024-07-09-14-17-36-S2EF-example
+  logs_dir: ./logs/tensorboard/2024-07-10-16-34-08-S2EF-example
   print_every: 5
-  results_dir: ./results/2024-07-09-14-17-36-S2EF-example
+  results_dir: ./results/2024-07-10-16-34-08-S2EF-example
   seed: 0
-  timestamp_id: 2024-07-09-14-17-36-S2EF-example
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-34-08-S2EF-example
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: lmdb
   grad_target_mean: 0.0
@@ -2419,28 +2419,28 @@ 
Create the trainer
2024-07-09 14:18:24 (INFO): Loading dataset: lmdb
+
2024-07-10 16:35:10 (INFO): Loading dataset: lmdb
 

 

-
2024-07-09 14:18:24 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:35:10 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:18:24 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:35:10 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:18:24 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:35:10 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:18:24 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:35:10 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:18:24 (INFO): Loading model: gemnet_oc
+
2024-07-10 16:35:10 (INFO): Loading model: gemnet_oc
 

 

-
2024-07-09 14:18:25 (INFO): Loaded GemNetOC with 2596214 parameters.
+
2024-07-10 16:35:11 (INFO): Loaded GemNetOC with 2596214 parameters.
 

 

-
2024-07-09 14:18:25 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:35:11 (WARNING): log_summary for Tensorboard not supported
 

 

 

@@ -2463,144 +2463,144 @@ 
Train the model
2024-07-09 14:18:30 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.37e+01, forcesx_mae: 4.54e-01, forcesy_mae: 6.14e-01, forcesz_mae: 7.50e-01, forces_mae: 6.06e-01, forces_cosine_similarity: 1.12e-02, forces_magnitude_error: 1.07e+00, loss: 1.06e+02, lr: 5.00e-04, epoch: 5.00e-02, step: 5.00e+00
+
2024-07-10 16:35:17 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.37e+01, forcesx_mae: 4.54e-01, forcesy_mae: 6.14e-01, forcesz_mae: 7.50e-01, forces_mae: 6.06e-01, forces_cosine_similarity: 1.12e-02, forces_magnitude_error: 1.07e+00, loss: 1.06e+02, lr: 5.00e-04, epoch: 5.00e-02, step: 5.00e+00
 

 

-
2024-07-09 14:18:36 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.22e+01, forcesx_mae: 2.45e-01, forcesy_mae: 6.06e-01, forcesz_mae: 4.26e-01, forces_mae: 4.26e-01, forces_cosine_similarity: -1.76e-02, forces_magnitude_error: 7.53e-01, loss: 6.92e+01, lr: 5.00e-04, epoch: 1.00e-01, step: 1.00e+01
+
2024-07-10 16:35:23 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.22e+01, forcesx_mae: 2.45e-01, forcesy_mae: 6.06e-01, forcesz_mae: 4.26e-01, forces_mae: 4.26e-01, forces_cosine_similarity: -1.76e-02, forces_magnitude_error: 7.53e-01, loss: 6.92e+01, lr: 5.00e-04, epoch: 1.00e-01, step: 1.00e+01
 

 

-
2024-07-09 14:18:41 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.07e+01, forcesx_mae: 3.58e-01, forcesy_mae: 6.73e-01, forcesz_mae: 5.27e-01, forces_mae: 5.19e-01, forces_cosine_similarity: -4.96e-02, forces_magnitude_error: 6.64e-01, loss: 8.13e+01, lr: 5.00e-04, epoch: 1.50e-01, step: 1.50e+01
+
2024-07-10 16:35:28 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.07e+01, forcesx_mae: 3.58e-01, forcesy_mae: 6.73e-01, forcesz_mae: 5.27e-01, forces_mae: 5.19e-01, forces_cosine_similarity: -4.96e-02, forces_magnitude_error: 6.64e-01, loss: 8.13e+01, lr: 5.00e-04, epoch: 1.50e-01, step: 1.50e+01
 

 

-
2024-07-09 14:18:47 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.78e+00, forcesx_mae: 2.21e-01, forcesy_mae: 3.42e-01, forcesz_mae: 2.78e-01, forces_mae: 2.80e-01, forces_cosine_similarity: -8.22e-03, forces_magnitude_error: 4.00e-01, loss: 3.78e+01, lr: 5.00e-04, epoch: 2.00e-01, step: 2.00e+01
+
2024-07-10 16:35:33 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.78e+00, forcesx_mae: 2.21e-01, forcesy_mae: 3.42e-01, forcesz_mae: 2.78e-01, forces_mae: 2.80e-01, forces_cosine_similarity: -8.22e-03, forces_magnitude_error: 4.00e-01, loss: 3.78e+01, lr: 5.00e-04, epoch: 2.00e-01, step: 2.00e+01
 

 

-
2024-07-09 14:18:52 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 6.92e+00, forcesx_mae: 1.22e-01, forcesy_mae: 1.55e-01, forcesz_mae: 1.62e-01, forces_mae: 1.46e-01, forces_cosine_similarity: 1.52e-03, forces_magnitude_error: 1.70e-01, loss: 2.28e+01, lr: 5.00e-04, epoch: 2.50e-01, step: 2.50e+01
+
2024-07-10 16:35:39 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 6.92e+00, forcesx_mae: 1.22e-01, forcesy_mae: 1.55e-01, forcesz_mae: 1.62e-01, forces_mae: 1.46e-01, forces_cosine_similarity: 1.52e-03, forces_magnitude_error: 1.70e-01, loss: 2.28e+01, lr: 5.00e-04, epoch: 2.50e-01, step: 2.50e+01
 

 

-
2024-07-09 14:18:57 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.86e+00, forcesx_mae: 1.02e-01, forcesy_mae: 1.38e-01, forcesz_mae: 1.65e-01, forces_mae: 1.35e-01, forces_cosine_similarity: -2.59e-02, forces_magnitude_error: 1.53e-01, loss: 2.05e+01, lr: 5.00e-04, epoch: 3.00e-01, step: 3.00e+01
+
2024-07-10 16:35:44 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.86e+00, forcesx_mae: 1.02e-01, forcesy_mae: 1.38e-01, forcesz_mae: 1.65e-01, forces_mae: 1.35e-01, forces_cosine_similarity: -2.59e-02, forces_magnitude_error: 1.53e-01, loss: 2.05e+01, lr: 5.00e-04, epoch: 3.00e-01, step: 3.00e+01
 

 

-
2024-07-09 14:19:02 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.40e+00, forcesx_mae: 4.77e-02, forcesy_mae: 5.14e-02, forcesz_mae: 6.43e-02, forces_mae: 5.45e-02, forces_cosine_similarity: 1.31e-01, forces_magnitude_error: 6.22e-02, loss: 8.02e+00, lr: 5.00e-04, epoch: 3.50e-01, step: 3.50e+01
+
2024-07-10 16:35:49 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.40e+00, forcesx_mae: 4.77e-02, forcesy_mae: 5.14e-02, forcesz_mae: 6.43e-02, forces_mae: 5.45e-02, forces_cosine_similarity: 1.31e-01, forces_magnitude_error: 6.22e-02, loss: 8.02e+00, lr: 5.00e-04, epoch: 3.50e-01, step: 3.50e+01
 

 

-
2024-07-09 14:19:08 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.24e+00, forcesx_mae: 9.29e-02, forcesy_mae: 1.05e-01, forcesz_mae: 1.26e-01, forces_mae: 1.08e-01, forces_cosine_similarity: 1.88e-01, forces_magnitude_error: 1.44e-01, loss: 1.58e+01, lr: 5.00e-04, epoch: 4.00e-01, step: 4.00e+01
+
2024-07-10 16:35:54 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.24e+00, forcesx_mae: 9.29e-02, forcesy_mae: 1.05e-01, forcesz_mae: 1.26e-01, forces_mae: 1.08e-01, forces_cosine_similarity: 1.88e-01, forces_magnitude_error: 1.44e-01, loss: 1.58e+01, lr: 5.00e-04, epoch: 4.00e-01, step: 4.00e+01
 

 

-
2024-07-09 14:19:13 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 5.25e+00, forcesx_mae: 1.35e-01, forcesy_mae: 1.87e-01, forcesz_mae: 2.25e-01, forces_mae: 1.83e-01, forces_cosine_similarity: 2.66e-01, forces_magnitude_error: 2.86e-01, loss: 2.66e+01, lr: 5.00e-04, epoch: 4.50e-01, step: 4.50e+01
+
2024-07-10 16:36:00 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 5.25e+00, forcesx_mae: 1.35e-01, forcesy_mae: 1.87e-01, forcesz_mae: 2.25e-01, forces_mae: 1.83e-01, forces_cosine_similarity: 2.66e-01, forces_magnitude_error: 2.86e-01, loss: 2.66e+01, lr: 5.00e-04, epoch: 4.50e-01, step: 4.50e+01
 

 

-
2024-07-09 14:19:18 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.42e+00, forcesx_mae: 8.28e-02, forcesy_mae: 1.02e-01, forcesz_mae: 1.43e-01, forces_mae: 1.09e-01, forces_cosine_similarity: 1.62e-01, forces_magnitude_error: 1.69e-01, loss: 1.48e+01, lr: 5.00e-04, epoch: 5.00e-01, step: 5.00e+01
+
2024-07-10 16:36:05 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.42e+00, forcesx_mae: 8.28e-02, forcesy_mae: 1.02e-01, forcesz_mae: 1.43e-01, forces_mae: 1.09e-01, forces_cosine_similarity: 1.62e-01, forces_magnitude_error: 1.69e-01, loss: 1.48e+01, lr: 5.00e-04, epoch: 5.00e-01, step: 5.00e+01
 

 

-
2024-07-09 14:19:23 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.76e+00, forcesx_mae: 1.67e-01, forcesy_mae: 1.72e-01, forcesz_mae: 2.52e-01, forces_mae: 1.97e-01, forces_cosine_similarity: 3.22e-01, forces_magnitude_error: 3.54e-01, loss: 2.73e+01, lr: 5.00e-04, epoch: 5.50e-01, step: 5.50e+01
+
2024-07-10 16:36:10 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.76e+00, forcesx_mae: 1.67e-01, forcesy_mae: 1.72e-01, forcesz_mae: 2.52e-01, forces_mae: 1.97e-01, forces_cosine_similarity: 3.22e-01, forces_magnitude_error: 3.54e-01, loss: 2.73e+01, lr: 5.00e-04, epoch: 5.50e-01, step: 5.50e+01
 

 

-
2024-07-09 14:19:29 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.39e+00, forcesx_mae: 2.59e-02, forcesy_mae: 3.27e-02, forcesz_mae: 4.49e-02, forces_mae: 3.45e-02, forces_cosine_similarity: 1.68e-01, forces_magnitude_error: 4.51e-02, loss: 5.40e+00, lr: 5.00e-04, epoch: 6.00e-01, step: 6.00e+01
+
2024-07-10 16:36:15 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.39e+00, forcesx_mae: 2.59e-02, forcesy_mae: 3.27e-02, forcesz_mae: 4.49e-02, forces_mae: 3.45e-02, forces_cosine_similarity: 1.68e-01, forces_magnitude_error: 4.51e-02, loss: 5.40e+00, lr: 5.00e-04, epoch: 6.00e-01, step: 6.00e+01
 

 

-
2024-07-09 14:19:34 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 5.01e+00, forcesx_mae: 3.09e-01, forcesy_mae: 5.03e-01, forcesz_mae: 3.94e-01, forces_mae: 4.02e-01, forces_cosine_similarity: 4.33e-01, forces_magnitude_error: 7.60e-01, loss: 5.12e+01, lr: 5.00e-04, epoch: 6.50e-01, step: 6.50e+01
+
2024-07-10 16:36:21 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 5.01e+00, forcesx_mae: 3.09e-01, forcesy_mae: 5.03e-01, forcesz_mae: 3.94e-01, forces_mae: 4.02e-01, forces_cosine_similarity: 4.33e-01, forces_magnitude_error: 7.60e-01, loss: 5.12e+01, lr: 5.00e-04, epoch: 6.50e-01, step: 6.50e+01
 

 

-
2024-07-09 14:19:39 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.36e+00, forcesx_mae: 1.42e-01, forcesy_mae: 1.55e-01, forcesz_mae: 2.27e-01, forces_mae: 1.75e-01, forces_cosine_similarity: 3.90e-01, forces_magnitude_error: 3.00e-01, loss: 2.43e+01, lr: 5.00e-04, epoch: 7.00e-01, step: 7.00e+01
+
2024-07-10 16:36:26 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.36e+00, forcesx_mae: 1.42e-01, forcesy_mae: 1.55e-01, forcesz_mae: 2.27e-01, forces_mae: 1.75e-01, forces_cosine_similarity: 3.90e-01, forces_magnitude_error: 3.00e-01, loss: 2.43e+01, lr: 5.00e-04, epoch: 7.00e-01, step: 7.00e+01
 

 

-
2024-07-09 14:19:44 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.84e+00, forcesx_mae: 8.30e-02, forcesy_mae: 1.45e-01, forcesz_mae: 9.24e-02, forces_mae: 1.07e-01, forces_cosine_similarity: 4.87e-02, forces_magnitude_error: 1.01e-01, loss: 1.33e+01, lr: 5.00e-04, epoch: 7.50e-01, step: 7.50e+01
+
2024-07-10 16:36:31 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.84e+00, forcesx_mae: 8.30e-02, forcesy_mae: 1.45e-01, forcesz_mae: 9.24e-02, forces_mae: 1.07e-01, forces_cosine_similarity: 4.87e-02, forces_magnitude_error: 1.01e-01, loss: 1.33e+01, lr: 5.00e-04, epoch: 7.50e-01, step: 7.50e+01
 

 

-
2024-07-09 14:19:50 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.56e+00, forcesx_mae: 1.39e-01, forcesy_mae: 2.00e-01, forcesz_mae: 1.79e-01, forces_mae: 1.72e-01, forces_cosine_similarity: 2.47e-01, forces_magnitude_error: 2.35e-01, loss: 2.32e+01, lr: 5.00e-04, epoch: 8.00e-01, step: 8.00e+01
+
2024-07-10 16:36:36 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.56e+00, forcesx_mae: 1.39e-01, forcesy_mae: 2.00e-01, forcesz_mae: 1.79e-01, forces_mae: 1.72e-01, forces_cosine_similarity: 2.47e-01, forces_magnitude_error: 2.35e-01, loss: 2.32e+01, lr: 5.00e-04, epoch: 8.00e-01, step: 8.00e+01
 

 

-
2024-07-09 14:19:55 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.04e+00, forcesx_mae: 2.15e-01, forcesy_mae: 8.73e-01, forcesz_mae: 3.32e-01, forces_mae: 4.73e-01, forces_cosine_similarity: 3.61e-01, forces_magnitude_error: 9.50e-01, loss: 5.55e+01, lr: 5.00e-04, epoch: 8.50e-01, step: 8.50e+01
+
2024-07-10 16:36:42 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.04e+00, forcesx_mae: 2.15e-01, forcesy_mae: 8.73e-01, forcesz_mae: 3.32e-01, forces_mae: 4.73e-01, forces_cosine_similarity: 3.61e-01, forces_magnitude_error: 9.50e-01, loss: 5.55e+01, lr: 5.00e-04, epoch: 8.50e-01, step: 8.50e+01
 

 

-
2024-07-09 14:20:00 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.04e+00, forcesx_mae: 5.54e-02, forcesy_mae: 8.34e-02, forcesz_mae: 7.28e-02, forces_mae: 7.05e-02, forces_cosine_similarity: 2.65e-01, forces_magnitude_error: 8.20e-02, loss: 9.80e+00, lr: 5.00e-04, epoch: 9.00e-01, step: 9.00e+01
+
2024-07-10 16:36:47 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.04e+00, forcesx_mae: 5.54e-02, forcesy_mae: 8.34e-02, forcesz_mae: 7.28e-02, forces_mae: 7.05e-02, forces_cosine_similarity: 2.65e-01, forces_magnitude_error: 8.20e-02, loss: 9.80e+00, lr: 5.00e-04, epoch: 9.00e-01, step: 9.00e+01
 

 

-
2024-07-09 14:20:05 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 6.24e-01, forcesx_mae: 3.87e-02, forcesy_mae: 4.64e-02, forcesz_mae: 6.17e-02, forces_mae: 4.89e-02, forces_cosine_similarity: 2.51e-01, forces_magnitude_error: 6.13e-02, loss: 6.77e+00, lr: 5.00e-04, epoch: 9.50e-01, step: 9.50e+01
+
2024-07-10 16:36:52 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 6.24e-01, forcesx_mae: 3.87e-02, forcesy_mae: 4.64e-02, forcesz_mae: 6.17e-02, forces_mae: 4.89e-02, forces_cosine_similarity: 2.51e-01, forces_magnitude_error: 6.13e-02, loss: 6.77e+00, lr: 5.00e-04, epoch: 9.50e-01, step: 9.50e+01
 

 

-
2024-07-09 14:20:11 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.63e-01, forcesx_mae: 6.36e-02, forcesy_mae: 1.05e-01, forcesz_mae: 7.27e-02, forces_mae: 8.05e-02, forces_cosine_similarity: 2.24e-01, forces_magnitude_error: 9.96e-02, loss: 1.01e+01, lr: 5.00e-04, epoch: 1.00e+00, step: 1.00e+02
+
2024-07-10 16:36:57 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.63e-01, forcesx_mae: 6.36e-02, forcesy_mae: 1.05e-01, forcesz_mae: 7.27e-02, forces_mae: 8.05e-02, forces_cosine_similarity: 2.24e-01, forces_magnitude_error: 9.96e-02, loss: 1.01e+01, lr: 5.00e-04, epoch: 1.00e+00, step: 1.00e+02
 

 

-
2024-07-09 14:20:11 (INFO): Evaluating on val.
+
2024-07-10 16:36:57 (INFO): Evaluating on val.
 

 

-
/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)
+
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/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)
 

 

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+
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-
2024-07-09 14:20:15 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 9.3699, forcesx_mae: 0.3033, forcesy_mae: 0.2619, forcesz_mae: 0.4725, forces_mae: 0.3459, forces_cosine_similarity: 0.0218, forces_magnitude_error: 0.4929, loss: 53.3609, epoch: 1.0000
+
2024-07-10 16:37:02 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 9.3699, forcesx_mae: 0.3033, forcesy_mae: 0.2619, forcesz_mae: 0.4725, forces_mae: 0.3459, forces_cosine_similarity: 0.0218, forces_magnitude_error: 0.4929, loss: 53.3609, epoch: 1.0000
 

 

 

@@ -2627,7 +2627,7 @@ 
Load the best checkpoint
-
'./checkpoints/2024-07-09-14-17-36-S2EF-example/best_checkpoint.pt'
+
'./checkpoints/2024-07-10-16-34-08-S2EF-example/best_checkpoint.pt'
 

 

 

@@ -2683,20 +2683,20 @@ 
Load the best checkpoint
-
2024-07-09 14:20:15 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:37:02 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:20:15 (INFO): amp: true
+
2024-07-10 16:37:02 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-19-44-S2EF-val-example
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-36-16-S2EF-val-example
+  commit: 36a17ad
   identifier: S2EF-val-example
-  logs_dir: ./logs/tensorboard/2024-07-09-14-19-44-S2EF-val-example
+  logs_dir: ./logs/tensorboard/2024-07-10-16-36-16-S2EF-val-example
   print_every: 5
-  results_dir: ./results/2024-07-09-14-19-44-S2EF-val-example
+  results_dir: ./results/2024-07-10-16-36-16-S2EF-val-example
   seed: 0
-  timestamp_id: 2024-07-09-14-19-44-S2EF-val-example
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-36-16-S2EF-val-example
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: lmdb
   grad_target_mean: 0.0
@@ -2868,37 +2868,37 @@ 
Load the best checkpoint
2024-07-09 14:20:15 (INFO): Loading dataset: lmdb
+
2024-07-10 16:37:02 (INFO): Loading dataset: lmdb
 

 

-
2024-07-09 14:20:15 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:37:02 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:20:15 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:37:02 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:20:15 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:37:02 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:20:15 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:37:02 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:20:15 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:37:02 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:20:15 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:37:02 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:20:15 (INFO): Loading model: gemnet_oc
+
2024-07-10 16:37:02 (INFO): Loading model: gemnet_oc
 

 

-
2024-07-09 14:20:16 (INFO): Loaded GemNetOC with 2596214 parameters.
+
2024-07-10 16:37:03 (INFO): Loaded GemNetOC with 2596214 parameters.
 

 

-
2024-07-09 14:20:16 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:37:03 (WARNING): log_summary for Tensorboard not supported
 

 

-
2024-07-09 14:20:16 (INFO): Loading checkpoint from: ./checkpoints/2024-07-09-14-17-36-S2EF-example/best_checkpoint.pt
+
2024-07-10 16:37:03 (INFO): Loading checkpoint from: ./checkpoints/2024-07-10-16-34-08-S2EF-example/best_checkpoint.pt
 

 

 

@@ -2914,7 +2914,7 @@ 
Run on the test set
-
2024-07-09 14:20:16 (INFO): Predicting on test.
+
2024-07-10 16:37:03 (INFO): Predicting on test.
 

 

 
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@@ -2928,70 +2928,70 @@ 
Run on the test set
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+
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+
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+
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+
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-
2024-07-09 14:20:21 (INFO): Writing results to ./results/2024-07-09-14-19-44-S2EF-val-example/s2ef_s2ef_results.npz
+
2024-07-10 16:37:08 (INFO): Writing results to ./results/2024-07-10-16-36-16-S2EF-val-example/s2ef_s2ef_results.npz
 

 

 

@@ -3181,20 +3181,20 @@ 
Define the Config
-
2024-07-09 14:20:21 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:37:08 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:20:21 (INFO): amp: true
+
2024-07-10 16:37:08 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-19-44-IS2RE-example
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-36-16-IS2RE-example
+  commit: 36a17ad
   identifier: IS2RE-example
-  logs_dir: ./logs/tensorboard/2024-07-09-14-19-44-IS2RE-example
+  logs_dir: ./logs/tensorboard/2024-07-10-16-36-16-IS2RE-example
   print_every: 5
-  results_dir: ./results/2024-07-09-14-19-44-IS2RE-example
+  results_dir: ./results/2024-07-10-16-36-16-IS2RE-example
   seed: 0
-  timestamp_id: 2024-07-09-14-19-44-IS2RE-example
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-36-16-IS2RE-example
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: single_point_lmdb
   key_mapping:
@@ -3313,40 +3313,40 @@ 
Define the Config
2024-07-09 14:20:21 (INFO): Loading dataset: single_point_lmdb
+
2024-07-10 16:37:08 (INFO): Loading dataset: single_point_lmdb
 

 

-
2024-07-09 14:20:21 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:37:08 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:20:21 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:37:08 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:20:21 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:37:08 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:20:21 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:37:08 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:20:21 (INFO): Loading model: gemnet_t
+
2024-07-10 16:37:08 (INFO): Loading model: gemnet_t
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_0_had not found in model
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_0_had not found in model
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_1_had not found in model
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_1_had not found in model
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_2_had not found in model
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_2_had not found in model
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_3_had not found in model
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_3_had not found in model
 

 

-
2024-07-09 14:20:22 (INFO): Loaded GemNetT with 22774037 parameters.
+
2024-07-10 16:37:09 (INFO): Loaded GemNetT with 22774037 parameters.
 

 

-
2024-07-09 14:20:22 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:37:09 (WARNING): log_summary for Tensorboard not supported
 

 

 

@@ -3361,28 +3361,28 @@ 
Train the Model
-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:20:22 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:37:09 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

 
/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()
@@ -3393,91 +3393,91 @@ 
Train the Model
2024-07-09 14:20:36 (INFO): energy_mae: 1.61e+03, energy_mse: 4.56e+06, energy_within_threshold: 0.00e+00, loss: 8.77e+02, lr: 1.00e-04, epoch: 5.00e-02, step: 5.00e+00
+
2024-07-10 16:37:23 (INFO): energy_mae: 1.61e+03, energy_mse: 4.56e+06, energy_within_threshold: 0.00e+00, loss: 8.77e+02, lr: 1.00e-04, epoch: 5.00e-02, step: 5.00e+00
 

 

-
2024-07-09 14:20:45 (INFO): energy_mae: 4.03e+03, energy_mse: 6.12e+07, energy_within_threshold: 0.00e+00, loss: 2.20e+03, lr: 1.00e-04, epoch: 1.00e-01, step: 1.00e+01
+
2024-07-10 16:37:32 (INFO): energy_mae: 4.03e+03, energy_mse: 6.12e+07, energy_within_threshold: 0.00e+00, loss: 2.19e+03, lr: 1.00e-04, epoch: 1.00e-01, step: 1.00e+01
 

 

-
2024-07-09 14:20:58 (INFO): energy_mae: 7.60e+02, energy_mse: 1.12e+06, energy_within_threshold: 0.00e+00, loss: 4.14e+02, lr: 1.00e-04, epoch: 1.50e-01, step: 1.50e+01
+
2024-07-10 16:37:45 (INFO): energy_mae: 7.61e+02, energy_mse: 1.12e+06, energy_within_threshold: 0.00e+00, loss: 4.14e+02, lr: 1.00e-04, epoch: 1.50e-01, step: 1.50e+01
 

 

-
2024-07-09 14:21:13 (INFO): energy_mae: 1.90e+03, energy_mse: 9.33e+06, energy_within_threshold: 0.00e+00, loss: 1.04e+03, lr: 1.00e-04, epoch: 2.00e-01, step: 2.00e+01
+
2024-07-10 16:38:00 (INFO): energy_mae: 1.91e+03, energy_mse: 9.38e+06, energy_within_threshold: 0.00e+00, loss: 1.04e+03, lr: 1.00e-04, epoch: 2.00e-01, step: 2.00e+01
 

 

-
2024-07-09 14:21:26 (INFO): energy_mae: 4.69e+02, energy_mse: 7.82e+05, energy_within_threshold: 0.00e+00, loss: 2.55e+02, lr: 1.00e-04, epoch: 2.50e-01, step: 2.50e+01
+
2024-07-10 16:38:14 (INFO): energy_mae: 4.70e+02, energy_mse: 7.88e+05, energy_within_threshold: 0.00e+00, loss: 2.56e+02, lr: 1.00e-04, epoch: 2.50e-01, step: 2.50e+01
 

 

-
2024-07-09 14:21:34 (INFO): energy_mae: 2.37e+02, energy_mse: 1.25e+05, energy_within_threshold: 0.00e+00, loss: 1.29e+02, lr: 1.00e-04, epoch: 3.00e-01, step: 3.00e+01
+
2024-07-10 16:38:22 (INFO): energy_mae: 2.40e+02, energy_mse: 1.27e+05, energy_within_threshold: 0.00e+00, loss: 1.30e+02, lr: 1.00e-04, epoch: 3.00e-01, step: 3.00e+01
 

 

-
2024-07-09 14:21:43 (INFO): energy_mae: 2.33e+03, energy_mse: 2.22e+07, energy_within_threshold: 0.00e+00, loss: 1.27e+03, lr: 1.00e-04, epoch: 3.50e-01, step: 3.50e+01
+
2024-07-10 16:38:31 (INFO): energy_mae: 2.28e+03, energy_mse: 2.16e+07, energy_within_threshold: 0.00e+00, loss: 1.24e+03, lr: 1.00e-04, epoch: 3.50e-01, step: 3.50e+01
 

 

-
2024-07-09 14:21:53 (INFO): energy_mae: 3.11e+03, energy_mse: 4.67e+07, energy_within_threshold: 0.00e+00, loss: 1.70e+03, lr: 1.00e-04, epoch: 4.00e-01, step: 4.00e+01
+
2024-07-10 16:38:40 (INFO): energy_mae: 3.07e+03, energy_mse: 4.55e+07, energy_within_threshold: 0.00e+00, loss: 1.67e+03, lr: 1.00e-04, epoch: 4.00e-01, step: 4.00e+01
 

 

-
2024-07-09 14:22:06 (INFO): energy_mae: 8.80e+02, energy_mse: 1.33e+06, energy_within_threshold: 0.00e+00, loss: 4.79e+02, lr: 1.00e-04, epoch: 4.50e-01, step: 4.50e+01
+
2024-07-10 16:38:53 (INFO): energy_mae: 7.54e+02, energy_mse: 8.98e+05, energy_within_threshold: 0.00e+00, loss: 4.10e+02, lr: 1.00e-04, epoch: 4.50e-01, step: 4.50e+01
 

 

-
2024-07-09 14:22:19 (INFO): energy_mae: 5.61e+02, energy_mse: 5.87e+05, energy_within_threshold: 0.00e+00, loss: 3.06e+02, lr: 1.00e-04, epoch: 5.00e-01, step: 5.00e+01
+
2024-07-10 16:39:06 (INFO): energy_mae: 5.44e+02, energy_mse: 5.44e+05, energy_within_threshold: 0.00e+00, loss: 2.96e+02, lr: 1.00e-04, epoch: 5.00e-01, step: 5.00e+01
 

 

-
2024-07-09 14:22:34 (INFO): energy_mae: 3.42e+02, energy_mse: 1.45e+05, energy_within_threshold: 0.00e+00, loss: 1.86e+02, lr: 1.00e-04, epoch: 5.50e-01, step: 5.50e+01
+
2024-07-10 16:39:22 (INFO): energy_mae: 3.08e+02, energy_mse: 1.06e+05, energy_within_threshold: 0.00e+00, loss: 1.67e+02, lr: 1.00e-04, epoch: 5.50e-01, step: 5.50e+01
 

 

-
2024-07-09 14:22:46 (INFO): energy_mae: 2.85e+02, energy_mse: 1.26e+05, energy_within_threshold: 0.00e+00, loss: 1.55e+02, lr: 1.00e-04, epoch: 6.00e-01, step: 6.00e+01
+
2024-07-10 16:39:33 (INFO): energy_mae: 2.85e+02, energy_mse: 1.39e+05, energy_within_threshold: 0.00e+00, loss: 1.55e+02, lr: 1.00e-04, epoch: 6.00e-01, step: 6.00e+01
 

 

-
2024-07-09 14:22:59 (INFO): energy_mae: 5.36e+02, energy_mse: 5.07e+05, energy_within_threshold: 0.00e+00, loss: 2.92e+02, lr: 1.00e-04, epoch: 6.50e-01, step: 6.50e+01
+
2024-07-10 16:39:47 (INFO): energy_mae: 5.99e+02, energy_mse: 6.46e+05, energy_within_threshold: 0.00e+00, loss: 3.26e+02, lr: 1.00e-04, epoch: 6.50e-01, step: 6.50e+01
 

 

-
2024-07-09 14:23:17 (INFO): energy_mae: 2.06e+03, energy_mse: 1.72e+07, energy_within_threshold: 0.00e+00, loss: 1.12e+03, lr: 1.00e-04, epoch: 7.00e-01, step: 7.00e+01
+
2024-07-10 16:40:05 (INFO): energy_mae: 2.96e+03, energy_mse: 3.89e+07, energy_within_threshold: 0.00e+00, loss: 1.61e+03, lr: 1.00e-04, epoch: 7.00e-01, step: 7.00e+01
 

 

-
2024-07-09 14:23:29 (INFO): energy_mae: 3.07e+02, energy_mse: 1.36e+05, energy_within_threshold: 0.00e+00, loss: 1.67e+02, lr: 1.00e-04, epoch: 7.50e-01, step: 7.50e+01
+
2024-07-10 16:40:17 (INFO): energy_mae: 3.80e+02, energy_mse: 1.90e+05, energy_within_threshold: 0.00e+00, loss: 2.07e+02, lr: 1.00e-04, epoch: 7.50e-01, step: 7.50e+01
 

 

-
2024-07-09 14:23:41 (INFO): energy_mae: 5.34e+02, energy_mse: 8.20e+05, energy_within_threshold: 0.00e+00, loss: 2.91e+02, lr: 1.00e-04, epoch: 8.00e-01, step: 8.00e+01
+
2024-07-10 16:40:29 (INFO): energy_mae: 1.78e+03, energy_mse: 1.32e+07, energy_within_threshold: 0.00e+00, loss: 9.67e+02, lr: 1.00e-04, epoch: 8.00e-01, step: 8.00e+01
 

 

-
2024-07-09 14:23:50 (INFO): energy_mae: 1.49e+02, energy_mse: 2.83e+04, energy_within_threshold: 0.00e+00, loss: 8.11e+01, lr: 1.00e-04, epoch: 8.50e-01, step: 8.50e+01
+
2024-07-10 16:40:38 (INFO): energy_mae: 1.69e+02, energy_mse: 3.32e+04, energy_within_threshold: 0.00e+00, loss: 9.20e+01, lr: 1.00e-04, epoch: 8.50e-01, step: 8.50e+01
 

 

-
2024-07-09 14:23:59 (INFO): energy_mae: 1.84e+02, energy_mse: 6.79e+04, energy_within_threshold: 0.00e+00, loss: 1.00e+02, lr: 1.00e-04, epoch: 9.00e-01, step: 9.00e+01
+
2024-07-10 16:40:47 (INFO): energy_mae: 1.29e+02, energy_mse: 3.36e+04, energy_within_threshold: 0.00e+00, loss: 7.02e+01, lr: 1.00e-04, epoch: 9.00e-01, step: 9.00e+01
 

 

-
2024-07-09 14:24:11 (INFO): energy_mae: 4.36e+02, energy_mse: 3.10e+05, energy_within_threshold: 0.00e+00, loss: 2.37e+02, lr: 1.00e-04, epoch: 9.50e-01, step: 9.50e+01
+
2024-07-10 16:40:59 (INFO): energy_mae: 6.31e+02, energy_mse: 6.99e+05, energy_within_threshold: 0.00e+00, loss: 3.43e+02, lr: 1.00e-04, epoch: 9.50e-01, step: 9.50e+01
 

 

-
2024-07-09 14:24:20 (INFO): energy_mae: 1.41e+02, energy_mse: 3.09e+04, energy_within_threshold: 0.00e+00, loss: 7.68e+01, lr: 1.00e-04, epoch: 1.00e+00, step: 1.00e+02
+
2024-07-10 16:41:08 (INFO): energy_mae: 1.14e+02, energy_mse: 1.74e+04, energy_within_threshold: 0.00e+00, loss: 6.18e+01, lr: 1.00e-04, epoch: 1.00e+00, step: 1.00e+02
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:08 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:21 (INFO): Evaluating on val.
+
2024-07-10 16:41:08 (INFO): Evaluating on val.
 

 

 
device 0:   0%|          | 0/20 [00:00<?, ?it/s]
@@ -3491,43 +3491,43 @@ 
Train the Model
device 0:   5%|▌         | 1/20 [00:01<00:24,  1.28s/it]
+
device 0:   5%|▌         | 1/20 [00:01<00:24,  1.31s/it]
 

 

 
device 0:  10%|█         | 2/20 [00:02<00:26,  1.49s/it]
 

 

-
device 0:  15%|█▌        | 3/20 [00:04<00:23,  1.38s/it]
+
device 0:  15%|█▌        | 3/20 [00:04<00:23,  1.39s/it]
 

 

-
device 0:  20%|██        | 4/20 [00:04<00:16,  1.06s/it]
+
device 0:  20%|██        | 4/20 [00:04<00:17,  1.08s/it]
 

 

 
device 0:  25%|██▌       | 5/20 [00:05<00:15,  1.04s/it]
 

 

-
device 0:  30%|███       | 6/20 [00:06<00:14,  1.06s/it]
+
device 0:  30%|███       | 6/20 [00:06<00:14,  1.02s/it]
 

 

-
device 0:  35%|███▌      | 7/20 [00:07<00:12,  1.07it/s]
+
device 0:  35%|███▌      | 7/20 [00:07<00:11,  1.12it/s]
 

 

-
device 0:  40%|████      | 8/20 [00:10<00:19,  1.60s/it]
+
device 0:  40%|████      | 8/20 [00:10<00:18,  1.53s/it]
 

 

-
device 0:  45%|████▌     | 9/20 [00:11<00:14,  1.30s/it]
+
device 0:  45%|████▌     | 9/20 [00:10<00:13,  1.26s/it]
 

 

-
device 0:  50%|█████     | 10/20 [00:11<00:10,  1.07s/it]
+
device 0:  50%|█████     | 10/20 [00:11<00:10,  1.03s/it]
 

 

-
device 0:  55%|█████▌    | 11/20 [00:12<00:07,  1.14it/s]
+
device 0:  55%|█████▌    | 11/20 [00:11<00:07,  1.18it/s]
 

 

-
device 0:  60%|██████    | 12/20 [00:13<00:07,  1.12it/s]
+
device 0:  60%|██████    | 12/20 [00:12<00:07,  1.12it/s]
 

 

-
device 0:  65%|██████▌   | 13/20 [00:13<00:05,  1.31it/s]
+
device 0:  65%|██████▌   | 13/20 [00:13<00:05,  1.30it/s]
 

 

 
device 0:  70%|███████   | 14/20 [00:14<00:05,  1.13it/s]
@@ -3536,25 +3536,25 @@ 
Train the Model
device 0:  75%|███████▌  | 15/20 [00:15<00:04,  1.12it/s]
 

 

-
device 0:  80%|████████  | 16/20 [00:15<00:02,  1.53it/s]
+
device 0:  80%|████████  | 16/20 [00:15<00:02,  1.51it/s]
 

 

 
device 0:  85%|████████▌ | 17/20 [00:16<00:02,  1.25it/s]
 

 

-
device 0:  90%|█████████ | 18/20 [00:18<00:01,  1.06it/s]
+
device 0:  90%|█████████ | 18/20 [00:17<00:01,  1.07it/s]
 

 

-
device 0:  95%|█████████▌| 19/20 [00:19<00:01,  1.06s/it]
+
device 0:  95%|█████████▌| 19/20 [00:19<00:01,  1.05s/it]
 

 

-
device 0: 100%|██████████| 20/20 [00:20<00:00,  1.06it/s]
+
device 0: 100%|██████████| 20/20 [00:19<00:00,  1.07it/s]
 

 

-
device 0: 100%|██████████| 20/20 [00:20<00:00,  1.01s/it]
+
device 0: 100%|██████████| 20/20 [00:19<00:00,  1.00it/s]
 

 

-
2024-07-09 14:24:41 (INFO): energy_mae: 1992.0683, energy_mse: 17559798.7293, energy_within_threshold: 0.0000, loss: 1084.3499, epoch: 1.0000
+
2024-07-10 16:41:28 (INFO): energy_mae: 1807.6307, energy_mse: 12997164.7755, energy_within_threshold: 0.0000, loss: 983.9544, epoch: 1.0000
 

 

 

@@ -3576,7 +3576,7 @@ 
Load the best checkpoint
-
'./checkpoints/2024-07-09-14-19-44-IS2RE-example/best_checkpoint.pt'
+
'./checkpoints/2024-07-10-16-36-16-IS2RE-example/best_checkpoint.pt'
 

 

 

@@ -3630,20 +3630,20 @@ 
Load the best checkpoint
-
2024-07-09 14:24:41 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:41:29 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:24:41 (INFO): amp: true
+
2024-07-10 16:41:29 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-24-00-IS2RE-val-example
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-40-32-IS2RE-val-example
+  commit: 36a17ad
   identifier: IS2RE-val-example
-  logs_dir: ./logs/tensorboard/2024-07-09-14-24-00-IS2RE-val-example
+  logs_dir: ./logs/tensorboard/2024-07-10-16-40-32-IS2RE-val-example
   print_every: 5
-  results_dir: ./results/2024-07-09-14-24-00-IS2RE-val-example
+  results_dir: ./results/2024-07-10-16-40-32-IS2RE-val-example
   seed: 0
-  timestamp_id: 2024-07-09-14-24-00-IS2RE-val-example
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-40-32-IS2RE-val-example
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: single_point_lmdb
   key_mapping:
@@ -3764,49 +3764,49 @@ 
Load the best checkpoint
2024-07-09 14:24:41 (INFO): Loading dataset: single_point_lmdb
+
2024-07-10 16:41:29 (INFO): Loading dataset: single_point_lmdb
 

 

-
2024-07-09 14:24:41 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:29 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:41 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:29 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:41 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:29 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:41 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:29 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:41 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:29 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:41 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:29 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:41 (INFO): Loading model: gemnet_t
+
2024-07-10 16:41:29 (INFO): Loading model: gemnet_t
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_0_had not found in model
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_0_had not found in model
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_1_had not found in model
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_1_had not found in model
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_2_had not found in model
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_2_had not found in model
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_3_had not found in model
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_3_had not found in model
 

 

-
2024-07-09 14:24:42 (INFO): Loaded GemNetT with 22774037 parameters.
+
2024-07-10 16:41:30 (INFO): Loaded GemNetT with 22774037 parameters.
 

 

-
2024-07-09 14:24:42 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:41:30 (WARNING): log_summary for Tensorboard not supported
 

 

-
2024-07-09 14:24:42 (INFO): Loading checkpoint from: ./checkpoints/2024-07-09-14-19-44-IS2RE-example/best_checkpoint.pt
+
2024-07-10 16:41:30 (INFO): Loading checkpoint from: ./checkpoints/2024-07-10-16-36-16-IS2RE-example/best_checkpoint.pt
 

 

 

@@ -3822,31 +3822,31 @@ 
Test the model
-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_4_sum (out_blocks.4.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor OutBlock_5_sum (out_blocks.5.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor TripInteraction_4_had_rbf (int_blocks.3.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor TripInteraction_4_sum_cbf (int_blocks.3.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor AtomUpdate_4_sum (int_blocks.3.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor TripInteraction_5_had_rbf (int_blocks.4.trip_interaction.scale_rbf) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor TripInteraction_5_sum_cbf (int_blocks.4.trip_interaction.scale_cbf_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
+
2024-07-10 16:41:30 (WARNING): Scale factor AtomUpdate_5_sum (int_blocks.4.atom_update.scale_sum) is not fitted. Please make sure that you either (1) load a checkpoint with fitted scale factors, (2) explicitly load scale factors using the `model.scale_file` attribute, or (3) fit the scale factors using the `fit.py` script.
 

 

-
2024-07-09 14:24:42 (INFO): Predicting on test.
+
2024-07-10 16:41:30 (INFO): Predicting on test.
 

 

 
device 0:   0%|          | 0/20 [00:00<?, ?it/s]
@@ -3860,70 +3860,70 @@ 
Test the model
device 0:   5%|▌         | 1/20 [00:00<00:06,  3.01it/s]
+
device 0:   5%|▌         | 1/20 [00:00<00:06,  2.92it/s]
 

 

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+
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+
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+
device 0:  20%|██        | 4/20 [00:01<00:03,  4.26it/s]
 

 

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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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-
device 0: 100%|██████████| 20/20 [00:04<00:00,  4.87it/s]
+
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-
device 0: 100%|██████████| 20/20 [00:04<00:00,  4.46it/s]
+
device 0: 100%|██████████| 20/20 [00:04<00:00,  4.51it/s]
 

 

-
2024-07-09 14:24:47 (INFO): Writing results to ./results/2024-07-09-14-24-00-IS2RE-val-example/is2re_is2re_results.npz
+
2024-07-10 16:41:34 (INFO): Writing results to ./results/2024-07-10-16-40-32-IS2RE-val-example/is2re_is2re_results.npz
 

 

 

@@ -4004,7 +4004,7 @@ 
Download pretrained checkpoint
-
2024-07-09 14:24:47 (INFO): Checking local cache: /tmp/ocp_checkpoints/ for model GemNet-dT-S2EF-OC20-All
+
2024-07-10 16:41:34 (INFO): Checking local cache: /tmp/ocp_checkpoints/ for model GemNet-dT-S2EF-OC20-All
 

 

 

@@ -4138,20 +4138,20 @@ 
Create the trainer
-
2024-07-09 14:24:48 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:41:36 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:24:48 (INFO): amp: true
+
2024-07-10 16:41:36 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-24-00-is2rs-example
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-42-40-is2rs-example
+  commit: 36a17ad
   identifier: is2rs-example
-  logs_dir: ./logs/tensorboard/2024-07-09-14-24-00-is2rs-example
+  logs_dir: ./logs/tensorboard/2024-07-10-16-42-40-is2rs-example
   print_every: 5
-  results_dir: ./results/2024-07-09-14-24-00-is2rs-example
+  results_dir: ./results/2024-07-10-16-42-40-is2rs-example
   seed: 0
-  timestamp_id: 2024-07-09-14-24-00-is2rs-example
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-42-40-is2rs-example
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: lmdb
   key_mapping:
@@ -4264,34 +4264,34 @@ 
Create the trainer
2024-07-09 14:24:48 (INFO): Loading dataset: lmdb
+
2024-07-10 16:41:36 (INFO): Loading dataset: lmdb
 

 

-
2024-07-09 14:24:48 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:36 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:48 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:36 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:48 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:36 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:48 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:36 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:48 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:41:36 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:24:48 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:41:36 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:24:48 (INFO): Loading model: gemnet_t
+
2024-07-10 16:41:36 (INFO): Loading model: gemnet_t
 

 

-
2024-07-09 14:24:50 (INFO): Loaded GemNetT with 31671825 parameters.
+
2024-07-10 16:41:37 (INFO): Loaded GemNetT with 31671825 parameters.
 

 

-
2024-07-09 14:24:50 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:41:37 (WARNING): log_summary for Tensorboard not supported
 

 

 

@@ -4306,7 +4306,7 @@ 
Load the best checkpoint
-
2024-07-09 14:24:50 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gemnet_t_direct_h512_all.pt
+
2024-07-10 16:41:37 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gemnet_t_direct_h512_all.pt
 

 

 

@@ -4322,483 +4322,483 @@ 
Run relaxations
-
2024-07-09 14:24:50 (INFO): Running ML-relaxations
-

-

-
  0%|          | 0/20 [00:00<?, ?it/s]
+
2024-07-10 16:41:37 (INFO): Running ML-relaxations
 

 

 
/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)
 

 

+
  0%|          | 0/20 [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)
 

 

-
2024-07-09 14:24:50 (INFO): Step   Fmax(eV/A)
+
2024-07-10 16:41:38 (INFO): Step   Fmax(eV/A)
 

 

-
2024-07-09 14:24:51 (INFO): 0 2.630
+
2024-07-10 16:41:39 (INFO): 0 2.630
 

 

-
2024-07-09 14:24:53 (INFO): 1 2.094
+
2024-07-10 16:41:40 (INFO): 1 2.094
 

 

-
2024-07-09 14:24:54 (INFO): 2 1.509
+
2024-07-10 16:41:41 (INFO): 2 1.509
 

 

-
2024-07-09 14:24:55 (INFO): 3 1.128
+
2024-07-10 16:41:42 (INFO): 3 1.128
 

 

-
2024-07-09 14:24:56 (INFO): 4 1.405
+
2024-07-10 16:41:43 (INFO): 4 1.405
 

 

-
2024-07-09 14:24:57 (INFO): 5 1.649
+
2024-07-10 16:41:44 (INFO): 5 1.649
 

 

-
2024-07-09 14:24:58 (INFO): 6 1.798
+
2024-07-10 16:41:45 (INFO): 6 1.798
 

 

-
2024-07-09 14:24:59 (INFO): 7 1.882
+
2024-07-10 16:41:46 (INFO): 7 1.882
 

 

-
2024-07-09 14:25:00 (INFO): 8 1.930
+
2024-07-10 16:41:48 (INFO): 8 1.930
 

 

-
2024-07-09 14:25:01 (INFO): 9 1.935
+
2024-07-10 16:41:49 (INFO): 9 1.935
 

 

-
2024-07-09 14:25:02 (INFO): 10 1.884
+
2024-07-10 16:41:50 (INFO): 10 1.884
 

 

-
2024-07-09 14:25:03 (INFO): 11 1.773
+
2024-07-10 16:41:51 (INFO): 11 1.773
 

 

-
2024-07-09 14:25:04 (INFO): 12 1.602
+
2024-07-10 16:41:52 (INFO): 12 1.602
 

 

-
2024-07-09 14:25:05 (INFO): 13 1.378
+
2024-07-10 16:41:53 (INFO): 13 1.378
 

 

-
2024-07-09 14:25:06 (INFO): 14 1.120
+
2024-07-10 16:41:54 (INFO): 14 1.120
 

 

-
2024-07-09 14:25:07 (INFO): 15 0.928
+
2024-07-10 16:41:55 (INFO): 15 0.928
 

 

-
2024-07-09 14:25:08 (INFO): 16 0.874
+
2024-07-10 16:41:56 (INFO): 16 0.874
 

 

-
2024-07-09 14:25:09 (INFO): 17 0.880
+
2024-07-10 16:41:57 (INFO): 17 0.880
 

 

-
2024-07-09 14:25:10 (INFO): 18 0.846
+
2024-07-10 16:41:58 (INFO): 18 0.846
 

 

-
2024-07-09 14:25:11 (INFO): 19 0.758
+
2024-07-10 16:41:59 (INFO): 19 0.758
 

 

-
2024-07-09 14:25:12 (INFO): 20 0.751
+
2024-07-10 16:42:00 (INFO): 20 0.751
 

 

-
2024-07-09 14:25:13 (INFO): 21 0.862
+
2024-07-10 16:42:01 (INFO): 21 0.862
 

 

-
2024-07-09 14:25:15 (INFO): 22 0.893
+
2024-07-10 16:42:02 (INFO): 22 0.893
 

 

-
2024-07-09 14:25:16 (INFO): 23 0.920
+
2024-07-10 16:42:03 (INFO): 23 0.920
 

 

-
2024-07-09 14:25:17 (INFO): 24 0.930
+
2024-07-10 16:42:04 (INFO): 24 0.930
 

 

-
2024-07-09 14:25:18 (INFO): 25 0.718
+
2024-07-10 16:42:05 (INFO): 25 0.718
 

 

-
2024-07-09 14:25:19 (INFO): 26 0.369
+
2024-07-10 16:42:06 (INFO): 26 0.369
 

 

-
2024-07-09 14:25:20 (INFO): 27 0.341
+
2024-07-10 16:42:07 (INFO): 27 0.341
 

 

-
2024-07-09 14:25:21 (INFO): 28 0.418
+
2024-07-10 16:42:08 (INFO): 28 0.418
 

 

-
2024-07-09 14:25:22 (INFO): 29 0.447
+
2024-07-10 16:42:09 (INFO): 29 0.447
 

 

-
2024-07-09 14:25:23 (INFO): 30 0.509
+
2024-07-10 16:42:10 (INFO): 30 0.509
 

 

-
2024-07-09 14:25:24 (INFO): 31 0.516
+
2024-07-10 16:42:11 (INFO): 31 0.516
 

 

-
2024-07-09 14:25:25 (INFO): 32 0.480
+
2024-07-10 16:42:13 (INFO): 32 0.480
 

 

-
2024-07-09 14:25:26 (INFO): 33 0.417
+
2024-07-10 16:42:14 (INFO): 33 0.417
 

 

-
2024-07-09 14:25:27 (INFO): 34 0.387
+
2024-07-10 16:42:15 (INFO): 34 0.387
 

 

-
2024-07-09 14:25:28 (INFO): 35 0.370
+
2024-07-10 16:42:16 (INFO): 35 0.370
 

 

-
2024-07-09 14:25:29 (INFO): 36 0.340
+
2024-07-10 16:42:17 (INFO): 36 0.340
 

 

-
2024-07-09 14:25:30 (INFO): 37 0.300
+
2024-07-10 16:42:18 (INFO): 37 0.300
 

 

-
2024-07-09 14:25:31 (INFO): 38 0.310
+
2024-07-10 16:42:19 (INFO): 38 0.310
 

 

-
2024-07-09 14:25:32 (INFO): 39 0.313
+
2024-07-10 16:42:20 (INFO): 39 0.313
 

 

-
2024-07-09 14:25:33 (INFO): 40 0.306
+
2024-07-10 16:42:21 (INFO): 40 0.306
 

 

-
2024-07-09 14:25:34 (INFO): 41 0.343
+
2024-07-10 16:42:22 (INFO): 41 0.343
 

 

-
2024-07-09 14:25:35 (INFO): 42 0.390
+
2024-07-10 16:42:23 (INFO): 42 0.390
 

 

-
2024-07-09 14:25:36 (INFO): 43 0.431
+
2024-07-10 16:42:24 (INFO): 43 0.431
 

 

-
2024-07-09 14:25:38 (INFO): 44 0.464
+
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-
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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-
  5%|▌         | 1/20 [02:35<49:10, 155.30s/it]
+
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-
  5%|▌         | 1/20 [02:35<49:11, 155.33s/it]
+
  5%|▌         | 1/20 [02:37<49:47, 157.24s/it]
 

 

-
2024-07-09 14:27:26 (INFO): Writing results to ./results/2024-07-09-14-24-00-is2rs-example/relaxed_positions.npz
+
2024-07-10 16:44:15 (INFO): Writing results to ./results/2024-07-10-16-42-40-is2rs-example/relaxed_positions.npz
 

 

-
2024-07-09 14:27:26 (INFO): {'positions_average_distance_within_threshold': {'total': 247, 'numel': 490, 'metric': 0.5040816326530613}, 'positions_mae': {'total': 23.29319953918457, 'numel': 60, 'metric': 0.38821999231974286}, 'positions_mse': {'total': 133.68051147460938, 'numel': 60, 'metric': 2.228008524576823}}
+
2024-07-10 16:44:15 (INFO): {'positions_average_distance_within_threshold': {'total': 247, 'numel': 490, 'metric': 0.5040816326530613}, 'positions_mae': {'total': 23.29319953918457, 'numel': 60, 'metric': 0.38821999231974286}, 'positions_mse': {'total': 133.68051147460938, 'numel': 60, 'metric': 2.228008524576823}}
 

 

-
2024-07-09 14:27:26 (INFO): {'energy_mae': {'total': 0.5329724550247192, 'numel': 1, 'metric': 0.5329724550247192}, 'energy_mse': {'total': 0.28405964374542236, 'numel': 1, 'metric': 0.28405964374542236}, 'energy_within_threshold': {'total': 0, 'numel': 1, 'metric': 0.0}}
+
2024-07-10 16:44:15 (INFO): {'energy_mae': {'total': 0.5329724550247192, 'numel': 1, 'metric': 0.5329724550247192}, 'energy_mse': {'total': 0.28405964374542236, 'numel': 1, 'metric': 0.28405964374542236}, 'energy_within_threshold': {'total': 0, 'numel': 1, 'metric': 0.0}}
 

 

 

@@ -5157,20 +5157,20 @@ 
Training the model
-
2024-07-09 14:27:27 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:44:17 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:27:27 (INFO): amp: true
+
2024-07-10 16:44:17 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-28-16-S2EF-simple
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-44-48-S2EF-simple
+  commit: 36a17ad
   identifier: S2EF-simple
-  logs_dir: ./logs/tensorboard/2024-07-09-14-28-16-S2EF-simple
+  logs_dir: ./logs/tensorboard/2024-07-10-16-44-48-S2EF-simple
   print_every: 5
-  results_dir: ./results/2024-07-09-14-28-16-S2EF-simple
+  results_dir: ./results/2024-07-10-16-44-48-S2EF-simple
   seed: 0
-  timestamp_id: 2024-07-09-14-28-16-S2EF-simple
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-44-48-S2EF-simple
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: trajectory_lmdb
   grad_target_mean: 0.0
@@ -5254,30 +5254,30 @@ 
Training the model
2024-07-09 14:27:27 (INFO): Loading dataset: trajectory_lmdb
+
2024-07-10 16:44:17 (INFO): Loading dataset: trajectory_lmdb
 

 

-
2024-07-09 14:27:27 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:44:17 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:27:27 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:44:17 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:27:27 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:44:17 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:27:27 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:44:17 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:27:27 (INFO): Loading model: simple
+
2024-07-10 16:44:17 (INFO): Loading model: simple
 

 

-
2024-07-09 14:27:27 (INFO): Loaded SimpleAtomEdgeModel with 185602 parameters.
+
2024-07-10 16:44:17 (INFO): Loaded SimpleAtomEdgeModel with 185602 parameters.
 

 

 
/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
   warnings.warn(_create_warning_msg(
-2024-07-09 14:27:27 (WARNING): log_summary for Tensorboard not supported
+2024-07-10 16:44:17 (WARNING): log_summary for Tensorboard not supported
 

 

 
/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()
@@ -5308,19 +5308,19 @@ 
Training the model
2024-07-09 14:27:31 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.87e+02, forcesx_mae: 3.03e-01, forcesy_mae: 4.22e-01, forcesz_mae: 1.41e+00, forces_mae: 7.13e-01, forces_cosine_similarity: 3.98e-02, forces_magnitude_error: 1.36e+00, loss: 1.90e+02, lr: 1.00e-04, epoch: 7.14e-01, step: 5.00e+00
+
2024-07-10 16:44:20 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.87e+02, forcesx_mae: 3.03e-01, forcesy_mae: 4.22e-01, forcesz_mae: 1.41e+00, forces_mae: 7.13e-01, forces_cosine_similarity: 3.98e-02, forces_magnitude_error: 1.36e+00, loss: 1.90e+02, lr: 1.00e-04, epoch: 7.14e-01, step: 5.00e+00
 

 

-
2024-07-09 14:27:31 (INFO): Evaluating on val.
-

-

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:44:21 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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)
 

@@ -5329,13 +5329,13 @@ 
Training the model
device 0:  33%|███▎      | 1/3 [00:00<00:00,  8.26it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00, 13.71it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:00<00:00,  7.57it/s]
+
device 0: 100%|██████████| 3/3 [00:00<00:00,  7.55it/s]
 

 

-
2024-07-09 14:27:32 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.3459, forcesx_mae: 0.2960, forcesy_mae: 0.2326, forcesz_mae: 0.8845, forces_mae: 0.4710, forces_cosine_similarity: -0.0539, forces_magnitude_error: 0.7951, loss: 98.3021, epoch: 1.0000
+
2024-07-10 16:44:22 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.3459, forcesx_mae: 0.2960, forcesy_mae: 0.2326, forcesz_mae: 0.8845, forces_mae: 0.4710, forces_cosine_similarity: -0.0539, forces_magnitude_error: 0.7951, loss: 98.3021, epoch: 1.0000
 

 

 

@@ -5369,10 +5369,10 @@ 
Training the model
2024-07-09 14:27:35 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.87e+02, forcesx_mae: 2.43e-01, forcesy_mae: 4.10e-01, forcesz_mae: 1.07e+00, forces_mae: 5.76e-01, forces_cosine_similarity: -2.68e-02, forces_magnitude_error: 1.04e+00, loss: 1.38e+02, lr: 1.00e-04, epoch: 1.43e+00, step: 1.00e+01
+
2024-07-10 16:44:25 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.87e+02, forcesx_mae: 2.43e-01, forcesy_mae: 4.10e-01, forcesz_mae: 1.07e+00, forces_mae: 5.76e-01, forces_cosine_similarity: -2.68e-02, forces_magnitude_error: 1.04e+00, loss: 1.38e+02, lr: 1.00e-04, epoch: 1.43e+00, step: 1.00e+01
 

 

-
2024-07-09 14:27:37 (INFO): Evaluating on val.
+
2024-07-10 16:44:26 (INFO): Evaluating on val.
 

 

 
/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()
@@ -5390,13 +5390,16 @@ 
Training the model
device 0:  67%|██████▋   | 2/3 [00:00<00:00, 12.94it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:00,  9.11it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:00<00:00,  7.19it/s]
+
device 0: 100%|██████████| 3/3 [00:00<00:00, 14.04it/s]
 

 

-
2024-07-09 14:27:38 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.0137, forcesx_mae: 0.3346, forcesy_mae: 0.2852, forcesz_mae: 0.9165, forces_mae: 0.5121, forces_cosine_similarity: -0.0387, forces_magnitude_error: 0.8785, loss: 100.9322, epoch: 2.0000
+
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.59it/s]
+

+

+
2024-07-10 16:44:27 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.0137, forcesx_mae: 0.3346, forcesy_mae: 0.2852, forcesz_mae: 0.9165, forces_mae: 0.5121, forces_cosine_similarity: -0.0387, forces_magnitude_error: 0.8785, loss: 100.9322, epoch: 2.0000
 

 

 

@@ -5430,20 +5433,20 @@ 
Training the model
2024-07-09 14:27:39 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.48e+02, forcesx_mae: 2.45e-01, forcesy_mae: 3.78e-01, forcesz_mae: 8.57e-01, forces_mae: 4.93e-01, forces_cosine_similarity: -9.92e-03, forces_magnitude_error: 8.38e-01, loss: 8.18e+01, lr: 1.00e-04, epoch: 2.14e+00, step: 1.50e+01
+
2024-07-10 16:44:29 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.48e+02, forcesx_mae: 2.45e-01, forcesy_mae: 3.78e-01, forcesz_mae: 8.57e-01, forces_mae: 4.93e-01, forces_cosine_similarity: -9.92e-03, forces_magnitude_error: 8.38e-01, loss: 8.18e+01, lr: 1.00e-04, epoch: 2.14e+00, step: 1.50e+01
 

 

-
2024-07-09 14:27:42 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.83e+01, forcesx_mae: 2.07e-01, forcesy_mae: 2.87e-01, forcesz_mae: 7.42e-01, forces_mae: 4.12e-01, forces_cosine_similarity: 5.41e-02, forces_magnitude_error: 6.96e-01, loss: 6.17e+01, lr: 1.00e-04, epoch: 2.86e+00, step: 2.00e+01
+
2024-07-10 16:44:32 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.83e+01, forcesx_mae: 2.07e-01, forcesy_mae: 2.87e-01, forcesz_mae: 7.42e-01, forces_mae: 4.12e-01, forces_cosine_similarity: 5.41e-02, forces_magnitude_error: 6.96e-01, loss: 6.17e+01, lr: 1.00e-04, epoch: 2.86e+00, step: 2.00e+01
 

 

-
2024-07-09 14:27:42 (INFO): Evaluating on val.
+
2024-07-10 16:44:32 (INFO): Evaluating on val.
 

 

-
/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)
+
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
 

 

-
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()
@@ -5454,13 +5457,16 @@ 
Training the model
device 0:  67%|██████▋   | 2/3 [00:00<00:00, 12.39it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:00,  7.78it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.73it/s]
+
device 0: 100%|██████████| 3/3 [00:00<00:00, 13.88it/s]
 

 

-
2024-07-09 14:27:43 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.1997, forcesx_mae: 0.3253, forcesy_mae: 0.2719, forcesz_mae: 0.9549, forces_mae: 0.5174, forces_cosine_similarity: -0.0524, forces_magnitude_error: 0.8993, loss: 101.7762, epoch: 3.0000
+
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.87it/s]
+

+

+
2024-07-10 16:44:33 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 181.1997, forcesx_mae: 0.3253, forcesy_mae: 0.2719, forcesz_mae: 0.9549, forces_mae: 0.5174, forces_cosine_similarity: -0.0524, forces_magnitude_error: 0.8993, loss: 101.7762, epoch: 3.0000
 

 

 

@@ -5494,10 +5500,10 @@ 
Training the model
2024-07-09 14:27:46 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.72e+01, forcesx_mae: 1.69e-01, forcesy_mae: 2.14e-01, forcesz_mae: 5.86e-01, forces_mae: 3.23e-01, forces_cosine_similarity: -5.92e-02, forces_magnitude_error: 4.86e-01, loss: 5.41e+01, lr: 1.00e-04, epoch: 3.57e+00, step: 2.50e+01
+
2024-07-10 16:44:36 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.72e+01, forcesx_mae: 1.69e-01, forcesy_mae: 2.14e-01, forcesz_mae: 5.86e-01, forces_mae: 3.23e-01, forces_cosine_similarity: -5.92e-02, forces_magnitude_error: 4.86e-01, loss: 5.41e+01, lr: 1.00e-04, epoch: 3.57e+00, step: 2.50e+01
 

 

-
2024-07-09 14:27:47 (INFO): Evaluating on val.
+
2024-07-10 16:44:38 (INFO): Evaluating on val.
 

 

 
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
@@ -5515,13 +5521,13 @@ 
Training the model
device 0:  33%|███▎      | 1/3 [00:00<00:00,  7.83it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00, 11.15it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.93it/s]
+
device 0: 100%|██████████| 3/3 [00:00<00:00,  7.25it/s]
 

 

-
2024-07-09 14:27:48 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 182.4001, forcesx_mae: 0.3315, forcesy_mae: 0.2815, forcesz_mae: 0.9607, forces_mae: 0.5246, forces_cosine_similarity: -0.0449, forces_magnitude_error: 0.9166, loss: 102.7514, epoch: 4.0000
+
2024-07-10 16:44:39 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 182.4001, forcesx_mae: 0.3315, forcesy_mae: 0.2815, forcesz_mae: 0.9607, forces_mae: 0.5246, forces_cosine_similarity: -0.0449, forces_magnitude_error: 0.9166, loss: 102.7514, epoch: 4.0000
 

 

 

@@ -5555,20 +5561,20 @@ 
Training the model
2024-07-09 14:27:51 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.02e+02, forcesx_mae: 1.51e-01, forcesy_mae: 2.59e-01, forcesz_mae: 3.91e-01, forces_mae: 2.67e-01, forces_cosine_similarity: 2.43e-02, forces_magnitude_error: 4.32e-01, loss: 5.62e+01, lr: 1.00e-04, epoch: 4.29e+00, step: 3.00e+01
+
2024-07-10 16:44:41 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.02e+02, forcesx_mae: 1.51e-01, forcesy_mae: 2.59e-01, forcesz_mae: 3.91e-01, forces_mae: 2.67e-01, forces_cosine_similarity: 2.43e-02, forces_magnitude_error: 4.32e-01, loss: 5.62e+01, lr: 1.00e-04, epoch: 4.29e+00, step: 3.00e+01
 

 

-
2024-07-09 14:27:53 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 4.68e+01, forcesx_mae: 1.76e-01, forcesy_mae: 2.78e-01, forcesz_mae: 3.97e-01, forces_mae: 2.84e-01, forces_cosine_similarity: -9.27e-03, forces_magnitude_error: 4.19e-01, loss: 3.96e+01, lr: 1.00e-04, epoch: 5.00e+00, step: 3.50e+01
+
2024-07-10 16:44:43 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 4.68e+01, forcesx_mae: 1.76e-01, forcesy_mae: 2.78e-01, forcesz_mae: 3.97e-01, forces_mae: 2.84e-01, forces_cosine_similarity: -9.27e-03, forces_magnitude_error: 4.19e-01, loss: 3.96e+01, lr: 1.00e-04, epoch: 5.00e+00, step: 3.50e+01
 

 

-
2024-07-09 14:27:53 (INFO): Evaluating on val.
+
2024-07-10 16:44:43 (INFO): Evaluating on val.
 

 

-
/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)
+
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
 

 

-
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()
@@ -5579,13 +5585,16 @@ 
Training the model
device 0:  67%|██████▋   | 2/3 [00:00<00:00, 12.80it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:00,  8.23it/s]
+

+

+
device 0: 100%|██████████| 3/3 [00:00<00:00, 14.48it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.58it/s]
+
device 0: 100%|██████████| 3/3 [00:00<00:00,  6.36it/s]
 

 

-
2024-07-09 14:27:54 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 185.2267, forcesx_mae: 0.3320, forcesy_mae: 0.2803, forcesz_mae: 0.9892, forces_mae: 0.5338, forces_cosine_similarity: -0.0477, forces_magnitude_error: 0.9421, loss: 104.6033, epoch: 5.0000
+
2024-07-10 16:44:44 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 185.2267, forcesx_mae: 0.3320, forcesy_mae: 0.2803, forcesz_mae: 0.9892, forces_mae: 0.5338, forces_cosine_similarity: -0.0477, forces_magnitude_error: 0.9421, loss: 104.6033, epoch: 5.0000
 

 

 

@@ -5658,20 +5667,20 @@ 
Incorporating triplets and training GemNet-T
-
2024-07-09 14:27:54 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:44:45 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:27:54 (INFO): amp: true
+
2024-07-10 16:44:45 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-28-16-S2EF-gemnet-t
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-44-48-S2EF-gemnet-t
+  commit: 36a17ad
   identifier: S2EF-gemnet-t
-  logs_dir: ./logs/tensorboard/2024-07-09-14-28-16-S2EF-gemnet-t
+  logs_dir: ./logs/tensorboard/2024-07-10-16-44-48-S2EF-gemnet-t
   print_every: 5
-  results_dir: ./results/2024-07-09-14-28-16-S2EF-gemnet-t
+  results_dir: ./results/2024-07-10-16-44-48-S2EF-gemnet-t
   seed: 0
-  timestamp_id: 2024-07-09-14-28-16-S2EF-gemnet-t
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-44-48-S2EF-gemnet-t
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: trajectory_lmdb
   grad_target_mean: 0.0
@@ -5780,62 +5789,62 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:27:54 (INFO): Loading dataset: trajectory_lmdb
+
2024-07-10 16:44:45 (INFO): Loading dataset: trajectory_lmdb
 

 

-
2024-07-09 14:27:54 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:44:45 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:27:54 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:44:45 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:27:54 (INFO): rank: 0: Sampler created...
+
2024-07-10 16:44:45 (INFO): rank: 0: Sampler created...
 

 

-
2024-07-09 14:27:54 (INFO): Batch balancing is disabled for single GPU training.
+
2024-07-10 16:44:45 (INFO): Batch balancing is disabled for single GPU training.
 

 

-
2024-07-09 14:27:54 (INFO): Loading model: gemnet_t
+
2024-07-10 16:44:45 (INFO): Loading model: gemnet_t
 

 

 
/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
   warnings.warn(_create_warning_msg(
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor TripInteraction_2_had_rbf not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor TripInteraction_2_had_rbf not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor TripInteraction_2_sum_cbf not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor TripInteraction_2_sum_cbf not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor AtomUpdate_2_sum not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor AtomUpdate_2_sum not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor TripInteraction_3_had_rbf not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor TripInteraction_3_had_rbf not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor TripInteraction_3_sum_cbf not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor TripInteraction_3_sum_cbf not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor AtomUpdate_3_sum not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor AtomUpdate_3_sum not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor OutBlock_2_sum not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor OutBlock_2_sum not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor OutBlock_2_had not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor OutBlock_2_had not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor OutBlock_3_sum not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor OutBlock_3_sum not found in model
 

 

-
2024-07-09 14:27:54 (WARNING): Scale factor OutBlock_3_had not found in model
+
2024-07-10 16:44:45 (WARNING): Scale factor OutBlock_3_had not found in model
 

 

-
2024-07-09 14:27:54 (INFO): Loaded GemNetT with 3360519 parameters.
+
2024-07-10 16:44:45 (INFO): Loaded GemNetT with 3360519 parameters.
 

 

-
2024-07-09 14:27:54 (WARNING): log_summary for Tensorboard not supported
+
2024-07-10 16:44:45 (WARNING): log_summary for Tensorboard not supported
 

 

 
/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()
@@ -5866,19 +5875,19 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:28:32 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.43e+01, forcesx_mae: 2.74e+00, forcesy_mae: 3.89e+00, forcesz_mae: 2.89e+00, forces_mae: 3.17e+00, forces_cosine_similarity: -3.46e-02, forces_magnitude_error: 6.00e+00, loss: 2.46e+02, lr: 1.00e-04, epoch: 7.14e-01, step: 5.00e+00
+
2024-07-10 16:45:22 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.43e+01, forcesx_mae: 2.74e+00, forcesy_mae: 3.89e+00, forcesz_mae: 2.89e+00, forces_mae: 3.17e+00, forces_cosine_similarity: -3.46e-02, forces_magnitude_error: 6.00e+00, loss: 2.46e+02, lr: 1.00e-04, epoch: 7.14e-01, step: 5.00e+00
 

 

-
2024-07-09 14:28:41 (INFO): Evaluating on val.
-

-

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:45:31 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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)
 

@@ -5887,19 +5896,19 @@ 
Incorporating triplets and training GemNet-T
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.86it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.88it/s]
 

 

-
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.29it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.49it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.08it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.10it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.18it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.30it/s]
 

 

-
2024-07-09 14:28:43 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 2.2356, forcesx_mae: 2.2589, forcesy_mae: 1.8025, forcesz_mae: 1.9335, forces_mae: 1.9983, forces_cosine_similarity: -0.1827, forces_magnitude_error: 3.7879, loss: 143.1054, epoch: 1.0000
+
2024-07-10 16:45:32 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 2.2356, forcesx_mae: 2.2589, forcesy_mae: 1.8025, forcesz_mae: 1.9335, forces_mae: 1.9983, forces_cosine_similarity: -0.1827, forces_magnitude_error: 3.7879, loss: 143.1054, epoch: 1.0000
 

 

 

@@ -5933,19 +5942,19 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:29:07 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.79e+01, forcesx_mae: 1.31e+00, forcesy_mae: 1.62e+00, forcesz_mae: 1.42e+00, forces_mae: 1.45e+00, forces_cosine_similarity: 1.16e-02, forces_magnitude_error: 2.67e+00, loss: 1.37e+02, lr: 1.00e-04, epoch: 1.43e+00, step: 1.00e+01
+
2024-07-10 16:45:56 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 8.79e+01, forcesx_mae: 1.31e+00, forcesy_mae: 1.62e+00, forcesz_mae: 1.42e+00, forces_mae: 1.45e+00, forces_cosine_similarity: 1.16e-02, forces_magnitude_error: 2.67e+00, loss: 1.37e+02, lr: 1.00e-04, epoch: 1.43e+00, step: 1.00e+01
 

 

-
2024-07-09 14:29:29 (INFO): Evaluating on val.
-

-

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:46:18 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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+

+

 
/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)
 

@@ -5954,19 +5963,19 @@ 
Incorporating triplets and training GemNet-T
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.85it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.81it/s]
 

 

-
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.45it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.43it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.15it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.12it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.16it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.30it/s]
 

 

-
2024-07-09 14:29:31 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.5906, forcesx_mae: 2.2641, forcesy_mae: 1.8005, forcesz_mae: 1.8728, forces_mae: 1.9791, forces_cosine_similarity: -0.1879, forces_magnitude_error: 3.7455, loss: 141.2371, epoch: 2.0000
+
2024-07-10 16:46:20 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.5906, forcesx_mae: 2.2641, forcesy_mae: 1.8005, forcesz_mae: 1.8728, forces_mae: 1.9791, forces_cosine_similarity: -0.1879, forces_magnitude_error: 3.7455, loss: 141.2371, epoch: 2.0000
 

 

 

@@ -6000,22 +6009,22 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:29:41 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.61e+01, forcesx_mae: 9.34e-01, forcesy_mae: 1.11e+00, forcesz_mae: 1.02e+00, forces_mae: 1.02e+00, forces_cosine_similarity: 1.95e-02, forces_magnitude_error: 1.79e+00, loss: 9.68e+01, lr: 1.00e-04, epoch: 2.14e+00, step: 1.50e+01
-

-

-
2024-07-09 14:30:15 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.94e+01, forcesx_mae: 6.71e-01, forcesy_mae: 7.64e-01, forcesz_mae: 7.18e-01, forces_mae: 7.18e-01, forces_cosine_similarity: 2.31e-02, forces_magnitude_error: 1.17e+00, loss: 6.32e+01, lr: 1.00e-04, epoch: 2.86e+00, step: 2.00e+01
+
2024-07-10 16:46:29 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 7.61e+01, forcesx_mae: 9.34e-01, forcesy_mae: 1.11e+00, forcesz_mae: 1.02e+00, forces_mae: 1.02e+00, forces_cosine_similarity: 1.95e-02, forces_magnitude_error: 1.79e+00, loss: 9.68e+01, lr: 1.00e-04, epoch: 2.14e+00, step: 1.50e+01
 

 

-
2024-07-09 14:30:17 (INFO): Evaluating on val.
+
2024-07-10 16:47:04 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 3.94e+01, forcesx_mae: 6.71e-01, forcesy_mae: 7.64e-01, forcesz_mae: 7.18e-01, forces_mae: 7.18e-01, forces_cosine_similarity: 2.31e-02, forces_magnitude_error: 1.17e+00, loss: 6.32e+01, lr: 1.00e-04, epoch: 2.86e+00, step: 2.00e+01
 

 

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:47:06 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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)
 

@@ -6024,19 +6033,19 @@ 
Incorporating triplets and training GemNet-T
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.77it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.79it/s]
 

 

-
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.24it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.48it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.96it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.12it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.04it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.28it/s]
 

 

-
2024-07-09 14:30:19 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 3.0236, forcesx_mae: 2.2729, forcesy_mae: 1.7737, forcesz_mae: 1.8415, forces_mae: 1.9627, forces_cosine_similarity: -0.1836, forces_magnitude_error: 3.7070, loss: 140.1182, epoch: 3.0000
+
2024-07-10 16:47:08 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 3.0236, forcesx_mae: 2.2729, forcesy_mae: 1.7737, forcesz_mae: 1.8415, forces_mae: 1.9627, forces_cosine_similarity: -0.1836, forces_magnitude_error: 3.7070, loss: 140.1182, epoch: 3.0000
 

 

 

@@ -6070,19 +6079,19 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:30:49 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 4.88e+01, forcesx_mae: 4.78e-01, forcesy_mae: 5.60e-01, forcesz_mae: 5.21e-01, forces_mae: 5.20e-01, forces_cosine_similarity: 4.65e-02, forces_magnitude_error: 8.15e-01, loss: 5.40e+01, lr: 1.00e-04, epoch: 3.57e+00, step: 2.50e+01
+
2024-07-10 16:47:38 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 4.88e+01, forcesx_mae: 4.78e-01, forcesy_mae: 5.60e-01, forcesz_mae: 5.21e-01, forces_mae: 5.20e-01, forces_cosine_similarity: 4.65e-02, forces_magnitude_error: 8.15e-01, loss: 5.40e+01, lr: 1.00e-04, epoch: 3.57e+00, step: 2.50e+01
 

 

-
2024-07-09 14:31:05 (INFO): Evaluating on val.
-

-

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:47:55 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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)
 

@@ -6091,19 +6100,19 @@ 
Incorporating triplets and training GemNet-T
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.86it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.89it/s]
 

 

-
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.41it/s]
+
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.37it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.05it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  3.09it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.09it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.24it/s]
 

 

-
2024-07-09 14:31:07 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.6152, forcesx_mae: 2.1384, forcesy_mae: 1.6930, forcesz_mae: 1.7895, forces_mae: 1.8736, forces_cosine_similarity: -0.1818, forces_magnitude_error: 3.5234, loss: 133.0624, epoch: 4.0000
+
2024-07-10 16:47:56 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.6152, forcesx_mae: 2.1384, forcesy_mae: 1.6930, forcesz_mae: 1.7895, forces_mae: 1.8736, forces_cosine_similarity: -0.1818, forces_magnitude_error: 3.5234, loss: 133.0624, epoch: 4.0000
 

 

 

@@ -6137,22 +6146,22 @@ 
Incorporating triplets and training GemNet-T
2024-07-09 14:31:24 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.94e+01, forcesx_mae: 4.26e-01, forcesy_mae: 5.73e-01, forcesz_mae: 4.49e-01, forces_mae: 4.82e-01, forces_cosine_similarity: 3.08e-02, forces_magnitude_error: 7.53e-01, loss: 4.45e+01, lr: 1.00e-04, epoch: 4.29e+00, step: 3.00e+01
+
2024-07-10 16:48:13 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 2.94e+01, forcesx_mae: 4.26e-01, forcesy_mae: 5.73e-01, forcesz_mae: 4.49e-01, forces_mae: 4.82e-01, forces_cosine_similarity: 3.08e-02, forces_magnitude_error: 7.53e-01, loss: 4.45e+01, lr: 1.00e-04, epoch: 4.29e+00, step: 3.00e+01
 

 

-
2024-07-09 14:31:53 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.90e+01, forcesx_mae: 3.97e-01, forcesy_mae: 5.02e-01, forcesz_mae: 4.63e-01, forces_mae: 4.54e-01, forces_cosine_similarity: 9.63e-02, forces_magnitude_error: 6.46e-01, loss: 3.94e+01, lr: 1.00e-04, epoch: 5.00e+00, step: 3.50e+01
+
2024-07-10 16:48:43 (INFO): energy_forces_within_threshold: 0.00e+00, energy_mae: 1.90e+01, forcesx_mae: 3.97e-01, forcesy_mae: 5.02e-01, forcesz_mae: 4.63e-01, forces_mae: 4.54e-01, forces_cosine_similarity: 9.63e-02, forces_magnitude_error: 6.46e-01, loss: 3.94e+01, lr: 1.00e-04, epoch: 5.00e+00, step: 3.50e+01
 

 

-
2024-07-09 14:31:53 (INFO): Evaluating on val.
-

-

-
device 0:   0%|          | 0/3 [00:00<?, ?it/s]
+
2024-07-10 16:48:43 (INFO): Evaluating on val.
 

 

 
/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)
 

 

+
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)
 

@@ -6161,19 +6170,19 @@ 
Incorporating triplets and training GemNet-T
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.92it/s]
+
device 0:  33%|███▎      | 1/3 [00:00<00:01,  1.64it/s]
 

 

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+
device 0:  67%|██████▋   | 2/3 [00:00<00:00,  2.35it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.91it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.92it/s]
 

 

-
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.07it/s]
+
device 0: 100%|██████████| 3/3 [00:01<00:00,  2.12it/s]
 

 

-
2024-07-09 14:31:55 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.9363, forcesx_mae: 2.1717, forcesy_mae: 1.7101, forcesz_mae: 1.7947, forces_mae: 1.8922, forces_cosine_similarity: -0.1857, forces_magnitude_error: 3.5687, loss: 134.6277, epoch: 5.0000
+
2024-07-10 16:48:45 (INFO): energy_forces_within_threshold: 0.0000, energy_mae: 1.9363, forcesx_mae: 2.1717, forcesy_mae: 1.7101, forcesz_mae: 1.7947, forces_mae: 1.8922, forces_cosine_similarity: -0.1857, forces_magnitude_error: 3.5687, loss: 134.6277, epoch: 5.0000
 

 

 

@@ -6201,7 +6210,7 @@ 
Download pretrained checkpoint
-
2024-07-09 14:31:56 (INFO): Checking local cache: /tmp/ocp_checkpoints/ for model GemNet-dT-S2EF-OC20-All
+
2024-07-10 16:48:45 (INFO): Checking local cache: /tmp/ocp_checkpoints/ for model GemNet-dT-S2EF-OC20-All
 

 

 

@@ -6245,20 +6254,20 @@ 
Using the OCP Calculator
-
2024-07-09 14:31:56 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+
2024-07-10 16:48:45 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
 

 

-
2024-07-09 14:31:56 (INFO): amp: false
+
2024-07-10 16:48:45 (INFO): amp: false
 cmd:
-  checkpoint_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/checkpoints/2024-07-09-14-32-32
-  commit: bf2b26e
+  checkpoint_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/checkpoints/2024-07-10-16-49-04
+  commit: 36a17ad
   identifier: ''
-  logs_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/logs/wandb/2024-07-09-14-32-32
+  logs_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/logs/wandb/2024-07-10-16-49-04
   print_every: 100
-  results_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/results/2024-07-09-14-32-32
+  results_dir: /home/runner/work/fairchem/fairchem/docs/legacy_tutorials/results/2024-07-10-16-49-04
   seed: null
-  timestamp_id: 2024-07-09-14-32-32
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-49-04
+  version: 0.1.dev1+g36a17ad
 dataset:
   format: trajectory_lmdb
   grad_target_mean: 0.0
@@ -6372,95 +6381,95 @@ 
Using the OCP Calculator
2024-07-09 14:31:56 (INFO): Loading model: gemnet_t
+
2024-07-10 16:48:45 (INFO): Loading model: gemnet_t
 

 

-
2024-07-09 14:31:58 (INFO): Loaded GemNetT with 31671825 parameters.
+
2024-07-10 16:48:47 (INFO): Loaded GemNetT with 31671825 parameters.
 

 

-
2024-07-09 14:31:58 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
+
2024-07-10 16:48:47 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
 

 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:31:58       -4.099784        1.567516
+BFGS:    0 16:48:47       -4.099784        1.567516
 

 

-
BFGS:    1 14:31:59       -4.244461        1.136988
+
BFGS:    1 16:48:48       -4.244461        1.136988
 

 

-
BFGS:    2 14:31:59       -4.403120        0.763538
+
BFGS:    2 16:48:48       -4.403120        0.763538
 

 

-
BFGS:    3 14:32:00       -4.503652        0.836403
+
BFGS:    3 16:48:49       -4.503652        0.836403
 

 

-
BFGS:    4 14:32:01       -4.558208        0.733873
+
BFGS:    4 16:48:50       -4.558208        0.733873
 

 

-
BFGS:    5 14:32:01       -4.592069        0.409536
+
BFGS:    5 16:48:50       -4.592069        0.409536
 

 

-
BFGS:    6 14:32:02       -4.619347        0.731239
+
BFGS:    6 16:48:51       -4.619347        0.731239
 

 

-
BFGS:    7 14:32:02       -4.671473        0.971220
+
BFGS:    7 16:48:52       -4.671473        0.971220
 

 

-
BFGS:    8 14:32:03       -4.796453        0.921123
+
BFGS:    8 16:48:52       -4.796453        0.921123
 

 

-
BFGS:    9 14:32:04       -4.957974        0.976140
+
BFGS:    9 16:48:53       -4.957974        0.976140
 

 

-
BFGS:   10 14:32:04       -5.109447        1.038363
+
BFGS:   10 16:48:53       -5.109447        1.038363
 

 

-
BFGS:   11 14:32:05       -5.295602        1.224861
+
BFGS:   11 16:48:54       -5.295602        1.224861
 

 

-
BFGS:   12 14:32:05       -5.498971        1.127107
+
BFGS:   12 16:48:54       -5.498971        1.127107
 

 

-
BFGS:   13 14:32:06       -5.618084        1.066881
+
BFGS:   13 16:48:55       -5.618084        1.066881
 

 

-
BFGS:   14 14:32:06       -5.737121        0.950872
+
BFGS:   14 16:48:56       -5.737121        0.950872
 

 

-
BFGS:   15 14:32:07       -5.901947        0.926001
+
BFGS:   15 16:48:56       -5.901947        0.926001
 

 

-
BFGS:   16 14:32:08       -6.076138        1.273703
+
BFGS:   16 16:48:57       -6.076138        1.273703
 

 

-
BFGS:   17 14:32:08       -6.198372        1.202876
+
BFGS:   17 16:48:57       -6.198372        1.202876
 

 

-
BFGS:   18 14:32:09       -6.250344        0.685223
+
BFGS:   18 16:48:58       -6.250344        0.685223
 

 

-
BFGS:   19 14:32:09       -6.254098        0.200815
+
BFGS:   19 16:48:58       -6.254098        0.200815
 

 

-
BFGS:   20 14:32:10       -6.293970        0.177886
+
BFGS:   20 16:48:59       -6.293970        0.177886
 

 

-
BFGS:   21 14:32:10       -6.326332        0.229425
+
BFGS:   21 16:48:59       -6.326332        0.229425
 

 

-
BFGS:   22 14:32:11       -6.324463        0.170005
+
BFGS:   22 16:49:00       -6.324463        0.170005
 

 

-
BFGS:   23 14:32:11       -6.321269        0.101603
+
BFGS:   23 16:49:00       -6.321269        0.101603
 

 

-
BFGS:   24 14:32:12       -6.328320        0.084661
+
BFGS:   24 16:49:01       -6.328320        0.084661
 

 

-
BFGS:   25 14:32:13       -6.331771        0.058621
+
BFGS:   25 16:49:02       -6.331771        0.058621
 

 

-
BFGS:   26 14:32:13       -6.331944        0.044489
+
BFGS:   26 16:49:02       -6.331944        0.044489
 

 

 
True
@@ -6689,13 +6698,10 @@ 
Structure to Energy and Forces (S2EF) LMDBs
  0%|          | 0/101 [00:00<?, ?it/s]
 

 

-
 37%|███▋      | 37/101 [00:00<00:00, 369.84it/s]
-

-

-
 87%|████████▋ | 88/101 [00:00<00:00, 450.85it/s]
+
 54%|█████▍    | 55/101 [00:00<00:00, 544.79it/s]
 

 

-
100%|██████████| 101/101 [00:00<00:00, 445.93it/s]
+
100%|██████████| 101/101 [00:00<00:00, 559.54it/s]
 

 

 

diff --git a/legacy_tutorials/data_preprocessing.html b/legacy_tutorials/data_preprocessing.html
index 1aa40ac5c..abe1cdd80 100644
--- a/legacy_tutorials/data_preprocessing.html
+++ b/legacy_tutorials/data_preprocessing.html
@@ -669,7 +669,7 @@ 
Generate toy dataset: Relaxation of CO on Cu
-
/tmp/ipykernel_4424/901556023.py:8: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4342/901556023.py:8: DeprecationWarning: Please use atoms.calc = calc
   adslab.set_calculator(EMT())
 

 

diff --git a/legacy_tutorials/data_visualization.html b/legacy_tutorials/data_visualization.html
index e5454c52a..f95c85e8d 100644
--- a/legacy_tutorials/data_visualization.html
+++ b/legacy_tutorials/data_visualization.html
@@ -757,311 +757,311 @@ 
Generating sample data
 

 
       Step     Time          Energy          fmax
-LBFGS:    0 14:32:30       15.804700        6.776430
+LBFGS:    0 16:49:17       15.804700        6.776430
 

 

-
LBFGS:    1 14:32:30       12.190607        4.323222
+
LBFGS:    1 16:49:17       12.190607        4.323222
 

 

-
LBFGS:    2 14:32:30       10.240169        2.265527
+
LBFGS:    2 16:49:17       10.240169        2.265527
 

 

-
LBFGS:    3 14:32:30        9.779223        0.937247
+
LBFGS:    3 16:49:17        9.779223        0.937247
 

 

-
LBFGS:    4 14:32:30        9.671525        0.770173
+
LBFGS:    4 16:49:17        9.671525        0.770173
 

 

-
LBFGS:    5 14:32:30        9.574461        0.663540
+
LBFGS:    5 16:49:17        9.574461        0.663540
 

 

-
LBFGS:    6 14:32:30        9.537502        0.571800
+
LBFGS:    6 16:49:17        9.537502        0.571800
 

 

-
LBFGS:    7 14:32:30        9.516673        0.446620
+
LBFGS:    7 16:49:17        9.516673        0.446620
 

 

-
LBFGS:    8 14:32:30        9.481330        0.461143
+
LBFGS:    8 16:49:17        9.481330        0.461143
 

 

-
LBFGS:    9 14:32:30        9.462255        0.293081
+
LBFGS:    9 16:49:17        9.462255        0.293081
 

 

-
LBFGS:   10 14:32:30        9.448937        0.249010
+
LBFGS:   10 16:49:17        9.448937        0.249010
 

 

-
LBFGS:   11 14:32:30        9.433813        0.237051
+
LBFGS:   11 16:49:17        9.433813        0.237051
 

 

-
LBFGS:   12 14:32:30        9.418884        0.260245
+
LBFGS:   12 16:49:17        9.418884        0.260245
 

 

-
LBFGS:   13 14:32:30        9.409649        0.253162
+
LBFGS:   13 16:49:17        9.409649        0.253162
 

 

-
LBFGS:   14 14:32:30        9.404838        0.162398
+
LBFGS:   14 16:49:17        9.404838        0.162398
 

 

-
LBFGS:   15 14:32:30        9.401753        0.182298
+
LBFGS:   15 16:49:17        9.401753        0.182298
 

 

-
LBFGS:   16 14:32:30        9.397314        0.259163
+
/tmp/ipykernel_4369/2542206394.py:19: DeprecationWarning: Please use atoms.calc = calc
+  adslab.set_calculator(EMT())
 

 

-
LBFGS:   17 14:32:30        9.387947        0.345022
+
LBFGS:   16 16:49:17        9.397314        0.259163
 

 

-
/tmp/ipykernel_4449/2542206394.py:19: DeprecationWarning: Please use atoms.calc = calc
-  adslab.set_calculator(EMT())
+
LBFGS:   17 16:49:17        9.387947        0.345022
 

 

-
LBFGS:   18 14:32:30        9.370825        0.407041
+
LBFGS:   18 16:49:17        9.370825        0.407041
 

 

-
LBFGS:   19 14:32:30        9.342222        0.433340
+
LBFGS:   19 16:49:17        9.342222        0.433340
 

 

-
LBFGS:   20 14:32:30        9.286822        0.500200
+
LBFGS:   20 16:49:17        9.286822        0.500200
 

 

-
LBFGS:   21 14:32:30        9.249910        0.524052
+
LBFGS:   21 16:49:17        9.249910        0.524052
 

 

-
LBFGS:   22 14:32:30        9.187179        0.511994
+
LBFGS:   22 16:49:17        9.187179        0.511994
 

 

-
LBFGS:   23 14:32:30        9.124811        0.571796
+
LBFGS:   23 16:49:17        9.124811        0.571796
 

 

-
LBFGS:   24 14:32:30        9.066185        0.540934
+
LBFGS:   24 16:49:17        9.066185        0.540934
 

 

-
LBFGS:   25 14:32:30        9.000116        1.079833
+
LBFGS:   25 16:49:17        9.000116        1.079833
 

 

-
LBFGS:   26 14:32:30        8.893632        0.752759
+
LBFGS:   26 16:49:17        8.893632        0.752759
 

 

-
LBFGS:   27 14:32:30        8.845939        0.332051
+
LBFGS:   27 16:49:17        8.845939        0.332051
 

 

-
LBFGS:   28 14:32:30        8.815173        0.251242
+
LBFGS:   28 16:49:17        8.815173        0.251242
 

 

-
LBFGS:   29 14:32:30        8.808721        0.214337
+
LBFGS:   29 16:49:17        8.808721        0.214337
 

 

-
LBFGS:   30 14:32:30        8.794643        0.154611
+
LBFGS:   30 16:49:17        8.794643        0.154611
 

 

-
LBFGS:   31 14:32:30        8.789162        0.201404
+
LBFGS:   31 16:49:17        8.789162        0.201404
 

 

-
LBFGS:   32 14:32:30        8.782320        0.175517
+
LBFGS:   32 16:49:17        8.782320        0.175517
 

 

-
LBFGS:   33 14:32:30        8.780394        0.103718
+
LBFGS:   33 16:49:17        8.780394        0.103718
 

 

-
LBFGS:   34 14:32:30        8.778410        0.107611
+
LBFGS:   34 16:49:17        8.778410        0.107611
 

 

-
LBFGS:   35 14:32:30        8.775079        0.179747
+
LBFGS:   35 16:49:17        8.775079        0.179747
 

 

-
LBFGS:   36 14:32:30        8.766987        0.333401
+
LBFGS:   36 16:49:17        8.766987        0.333401
 

 

-
LBFGS:   37 14:32:30        8.750249        0.530715
+
LBFGS:   37 16:49:17        8.750249        0.530715
 

 

-
LBFGS:   38 14:32:30        8.725928        0.685116
+
LBFGS:   38 16:49:17        8.725928        0.685116
 

 

-
LBFGS:   39 14:32:30        8.702312        0.582260
+
LBFGS:   39 16:49:17        8.702312        0.582260
 

 

-
LBFGS:   40 14:32:30        8.661515        0.399625
+
LBFGS:   40 16:49:17        8.661515        0.399625
 

 

-
LBFGS:   41 14:32:30        8.643432        0.558474
+
LBFGS:   41 16:49:17        8.643432        0.558474
 

 

-
LBFGS:   42 14:32:30        8.621201        0.367288
+
LBFGS:   42 16:49:17        8.621201        0.367288
 

 

-
LBFGS:   43 14:32:30        8.614414        0.139424
+
LBFGS:   43 16:49:17        8.614414        0.139424
 

 

-
LBFGS:   44 14:32:30        8.610785        0.137160
+
LBFGS:   44 16:49:17        8.610785        0.137160
 

 

-
LBFGS:   45 14:32:30        8.608134        0.146375
+
LBFGS:   45 16:49:17        8.608134        0.146375
 

 

-
LBFGS:   46 14:32:30        8.604928        0.119648
+
LBFGS:   46 16:49:17        8.604928        0.119648
 

 

-
LBFGS:   47 14:32:30        8.599151        0.135424
+
LBFGS:   47 16:49:17        8.599151        0.135424
 

 

-
LBFGS:   48 14:32:30        8.594063        0.147913
+
LBFGS:   48 16:49:17        8.594063        0.147913
 

 

-
LBFGS:   49 14:32:30        8.589493        0.153840
+
LBFGS:   49 16:49:17        8.589493        0.153840
 

 

-
LBFGS:   50 14:32:30        8.587274        0.088460
+
LBFGS:   50 16:49:17        8.587274        0.088460
 

 

-
LBFGS:   51 14:32:30        8.584633        0.093750
+
LBFGS:   51 16:49:17        8.584633        0.093750
 

 

-
LBFGS:   52 14:32:30        8.580239        0.140870
+
LBFGS:   52 16:49:17        8.580239        0.140870
 

 

-
LBFGS:   53 14:32:30        8.572938        0.254272
+
LBFGS:   53 16:49:17        8.572938        0.254272
 

 

-
LBFGS:   54 14:32:30        8.563343        0.291885
+
LBFGS:   54 16:49:17        8.563343        0.291885
 

 

-
LBFGS:   55 14:32:30        8.554117        0.196557
+
LBFGS:   55 16:49:17        8.554117        0.196557
 

 

-
LBFGS:   56 14:32:30        8.547597        0.129064
+
LBFGS:   56 16:49:17        8.547597        0.129064
 

 

-
LBFGS:   57 14:32:30        8.542086        0.128020
+
LBFGS:   57 16:49:17        8.542086        0.128020
 

 

-
LBFGS:   58 14:32:30        8.535432        0.098202
+
LBFGS:   58 16:49:17        8.535432        0.098202
 

 

-
LBFGS:   59 14:32:30        8.533622        0.127672
+
LBFGS:   59 16:49:17        8.533622        0.127672
 

 

-
LBFGS:   60 14:32:30        8.527487        0.116729
+
LBFGS:   60 16:49:18        8.527487        0.116729
 

 

-
LBFGS:   61 14:32:30        8.523863        0.121762
+
LBFGS:   61 16:49:18        8.523863        0.121762
 

 

-
LBFGS:   62 14:32:30        8.519229        0.130541
+
LBFGS:   62 16:49:18        8.519229        0.130541
 

 

-
LBFGS:   63 14:32:30        8.515424        0.101902
+
LBFGS:   63 16:49:18        8.515424        0.101902
 

 

-
LBFGS:   64 14:32:30        8.511240        0.212223
+
LBFGS:   64 16:49:18        8.511240        0.212223
 

 

-
LBFGS:   65 14:32:30        8.507967        0.266593
+
LBFGS:   65 16:49:18        8.507967        0.266593
 

 

-
LBFGS:   66 14:32:30        8.503903        0.237734
+
LBFGS:   66 16:49:18        8.503903        0.237734
 

 

-
LBFGS:   67 14:32:30        8.497575        0.162253
+
LBFGS:   67 16:49:18        8.497575        0.162253
 

 

-
LBFGS:   68 14:32:30        8.485434        0.202203
+
LBFGS:   68 16:49:18        8.485434        0.202203
 

 

-
LBFGS:   69 14:32:30        8.466738        0.215895
+
LBFGS:   69 16:49:18        8.466738        0.215895
 

 

-
LBFGS:   70 14:32:31        8.467607        0.334764
+
LBFGS:   70 16:49:18        8.467607        0.334764
 

 

-
LBFGS:   71 14:32:31        8.454037        0.106310
+
LBFGS:   71 16:49:18        8.454037        0.106310
 

 

-
LBFGS:   72 14:32:31        8.448980        0.119721
+
LBFGS:   72 16:49:18        8.448980        0.119721
 

 

-
LBFGS:   73 14:32:31        8.446550        0.099221
+
LBFGS:   73 16:49:18        8.446550        0.099221
 

 

-
LBFGS:   74 14:32:31        8.444705        0.056244
+
LBFGS:   74 16:49:18        8.444705        0.056244
 

 

-
LBFGS:   75 14:32:31        8.443403        0.038831
+
LBFGS:   75 16:49:18        8.443403        0.038831
 

 

-
LBFGS:   76 14:32:31        8.442646        0.054772
+
LBFGS:   76 16:49:18        8.442646        0.054772
 

 

-
LBFGS:   77 14:32:31        8.442114        0.061370
+
LBFGS:   77 16:49:18        8.442114        0.061370
 

 

-
LBFGS:   78 14:32:31        8.440960        0.058800
+
LBFGS:   78 16:49:18        8.440960        0.058800
 

 

-
LBFGS:   79 14:32:31        8.439820        0.048198
+
LBFGS:   79 16:49:18        8.439820        0.048198
 

 

-
LBFGS:   80 14:32:31        8.438600        0.051251
+
LBFGS:   80 16:49:18        8.438600        0.051251
 

 

-
LBFGS:   81 14:32:31        8.437429        0.054130
+
LBFGS:   81 16:49:18        8.437429        0.054130
 

 

-
LBFGS:   82 14:32:31        8.435695        0.067234
+
LBFGS:   82 16:49:18        8.435695        0.067234
 

 

-
LBFGS:   83 14:32:31        8.431957        0.085678
+
LBFGS:   83 16:49:18        8.431957        0.085678
 

 

-
LBFGS:   84 14:32:31        8.423485        0.133240
+
LBFGS:   84 16:49:18        8.423485        0.133240
 

 

-
LBFGS:   85 14:32:31        8.413846        0.207812
+
LBFGS:   85 16:49:18        8.413846        0.207812
 

 

-
LBFGS:   86 14:32:31        8.404849        0.178747
+
LBFGS:   86 16:49:18        8.404849        0.178747
 

 

-
LBFGS:   87 14:32:31        8.385339        0.169017
+
LBFGS:   87 16:49:18        8.385339        0.169017
 

 

-
LBFGS:   88 14:32:31        8.386849        0.187645
+
LBFGS:   88 16:49:18        8.386849        0.187645
 

 

-
LBFGS:   89 14:32:31        8.371078        0.118124
+
LBFGS:   89 16:49:18        8.371078        0.118124
 

 

-
LBFGS:   90 14:32:31        8.368801        0.094222
+
LBFGS:   90 16:49:18        8.368801        0.094222
 

 

-
LBFGS:   91 14:32:31        8.366226        0.066960
+
LBFGS:   91 16:49:18        8.366226        0.066960
 

 

-
LBFGS:   92 14:32:31        8.361680        0.054964
+
LBFGS:   92 16:49:18        8.361680        0.054964
 

 

-
LBFGS:   93 14:32:31        8.360631        0.047342
+
LBFGS:   93 16:49:18        8.360631        0.047342
 

 

-
LBFGS:   94 14:32:31        8.359692        0.024179
+
LBFGS:   94 16:49:18        8.359692        0.024179
 

 

-
LBFGS:   95 14:32:31        8.359361        0.015549
+
LBFGS:   95 16:49:18        8.359361        0.015549
 

 

-
LBFGS:   96 14:32:31        8.359163        0.014284
+
LBFGS:   96 16:49:18        8.359163        0.014284
 

 

-
LBFGS:   97 14:32:31        8.359102        0.015615
+
LBFGS:   97 16:49:18        8.359102        0.015615
 

 

-
LBFGS:   98 14:32:31        8.359048        0.015492
+
LBFGS:   98 16:49:18        8.359048        0.015492
 

 

-
LBFGS:   99 14:32:31        8.358986        0.014214
+
LBFGS:   99 16:49:18        8.358986        0.014214
 

 

-
LBFGS:  100 14:32:31        8.358921        0.013159
+
LBFGS:  100 16:49:18        8.358921        0.013159
 

 

 
/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/ase/io/extxyz.py:311: UserWarning: Skipping unhashable information adsorbate_info
@@ -1310,7 +1310,7 @@ 
Energy#

 

-
/tmp/ipykernel_4449/1528962.py:7: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4369/1528962.py:7: DeprecationWarning: Please use atoms.calc = calc
   raw_slab.set_calculator(EMT())
 

 

diff --git a/searchindex.js b/searchindex.js
index b85f34e07..2d6acfd7b 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"": [[202, "id1"], [202, "id2"]], "(Optional) Creating your own LMDBs for use in the OCP repository": [[219, "optional-creating-your-own-lmdbs-for-use-in-the-ocp-repository"]], "(Optional) Deduplicate structures": [[226, "optional-deduplicate-structures"]], "(Optional) OCP Calculator ": [[219, "optional-ocp-calculator"]], "(Optional) Visualize the results": [[230, "optional-visualize-the-results"]], "A clustering example": [[228, "a-clustering-example"]], "A diagnostic example": [[228, "a-diagnostic-example"]], "A simple vector search example": [[228, "a-simple-vector-search-example"]], "API Reference": [[185, "api-reference"]], "About the compute environment": [[231, "about-the-compute-environment"]], "Abstract": [[231, "abstract"]], "Acknowledgements": [[218, "acknowledgements"]], "Adding additional info to your Data objects": [[220, "adding-additional-info-to-your-data-objects"]], "Additional Resources": [[219, "additional-resources"]], "Additional packages": [[207, "additional-packages"]], "AdsorbML tutorial": [[226, "adsorbml-tutorial"]], "Adsorbate+catalyst system trajectories (optional download)": [[199, "adsorbate-catalyst-system-trajectories-optional-download"]], "Adsorbate-catalyst system to catalyst system mapping information": [[199, "adsorbate-catalyst-system-to-catalyst-system-mapping-information"]], "Adsorption energy": [[219, "adsorption-energy"]], "Advanced OCP usage": [[227, "advanced-ocp-usage"]], "Advanced usage": [[210, "advanced-usage"], [214, "advanced-usage"]], "Are predictions from FAIRChem models deterministic?": [[212, "are-predictions-from-fairchem-models-deterministic"]], "Atom and Edge Embeddings": [[219, "atom-and-edge-embeddings"]], "Atomic numbers": [[219, "atomic-numbers"], [221, "atomic-numbers"]], "Atomic symbols": [[219, "atomic-symbols"], [221, "atomic-symbols"]], "Attributes": [[1, "attributes"], [2, "attributes"], [4, "attributes"], [9, "attributes"], [10, "attributes"], [11, "attributes"], 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\ No newline at end of file
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\ No newline at end of file
diff --git a/tutorials/NRR/NRR_example.html b/tutorials/NRR/NRR_example.html
index 53abb569c..60017b83d 100644
--- a/tutorials/NRR/NRR_example.html
+++ b/tutorials/NRR/NRR_example.html
@@ -770,7 +770,7 @@ 
Work out a single example
-../../_images/cfcdc7e302775579c03049aef09d50bcdd1691a83bfa4ec1a20e1ac8536e0ce7.png
+../../_images/c2d46ce94f5bd95474bf0f35cece29b3531bc7d573c9c716bd1a2006c183352d.png
 

 

 

@@ -815,115 +815,25 @@ 
Run an ML relaxation
 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:33:29        1.037800        1.176177
+BFGS:    0 16:50:18        0.448873        0.407166
 

 

-
BFGS:    1 14:33:31        1.002681        1.068257
+
BFGS:    1 16:50:20        0.441975        0.386778
 

 

-
BFGS:    2 14:33:32        1.006755        1.913398
+
BFGS:    2 16:50:21        0.360472        0.144668
 

 

-
BFGS:    3 14:33:33        0.903462        0.382399
+
BFGS:    3 16:50:22        0.357210        0.107372
 

 

-
BFGS:    4 14:33:35        0.894873        0.215970
+
BFGS:    4 16:50:24        0.355165        0.066706
 

 

-
BFGS:    5 14:33:36        0.888588        0.347158
+
BFGS:    5 16:50:25        0.351798        0.029186
 

 

-
BFGS:    6 14:33:38        0.879683        0.411830
-

-

-
BFGS:    7 14:33:39        0.857418        0.335076
-

-

-
BFGS:    8 14:33:40        0.855428        0.173321
-

-

-
BFGS:    9 14:33:42        0.854550        0.152194
-

-

-
BFGS:   10 14:33:43        0.853380        0.179546
-

-

-
BFGS:   11 14:33:44        0.850853        0.234581
-

-

-
BFGS:   12 14:33:46        0.836197        0.300265
-

-

-
BFGS:   13 14:33:47        0.835686        0.358457
-

-

-
BFGS:   14 14:33:49        0.834531        0.357938
-

-

-
BFGS:   15 14:33:50        0.826909        0.288661
-

-

-
BFGS:   16 14:33:51        0.800643        0.423498
-

-

-
BFGS:   17 14:33:53        0.748434        0.565419
-

-

-
BFGS:   18 14:33:54        0.664296        0.666029
-

-

-
BFGS:   19 14:33:55        0.558007        0.670297
-

-

-
BFGS:   20 14:33:57        0.455442        0.692118
-

-

-
BFGS:   21 14:33:58        0.388982        0.674562
-

-

-
BFGS:   22 14:34:00        0.362901        0.459165
-

-

-
BFGS:   23 14:34:01        0.335746        0.407887
-

-

-
BFGS:   24 14:34:02        0.320631        0.442945
-

-

-
BFGS:   25 14:34:04        0.311231        0.422388
-

-

-
BFGS:   26 14:34:05        0.294369        0.327302
-

-

-
BFGS:   27 14:34:06        0.277074        0.245572
-

-

-
BFGS:   28 14:34:08        0.261314        0.273677
-

-

-
BFGS:   29 14:34:09        0.253480        0.263545
-

-

-
BFGS:   30 14:34:11        0.248171        0.230598
-

-

-
BFGS:   31 14:34:12        0.242258        0.171499
-

-

-
BFGS:   32 14:34:13        0.238967        0.084736
-

-

-
BFGS:   33 14:34:15        0.233828        0.078479
-

-

-
BFGS:   34 14:34:16        0.234281        0.056103
-

-

-
BFGS:   35 14:34:17        0.230993        0.041118
-

-

-
Elapsed time 49.5 seconds
+
Elapsed time 8.4 seconds
 

 

 

@@ -1053,42 +963,42 @@ 
Run all the systems
  Elapsed time: 29.4 seconds for data/oqmd-349719_H/0
+
  Elapsed time: 13.6 seconds for data/oqmd-349719_H/0
 Running data/oqmd-349719_H/1
 

 

-
  Elapsed time: 55.3 seconds for data/oqmd-349719_H/1
+
  Elapsed time: 56.4 seconds for data/oqmd-349719_H/1
 Running data/oqmd-349719_H/2
 

 

-
  Elapsed time: 18.5 seconds for data/oqmd-349719_H/2
+
  Elapsed time: 29.7 seconds for data/oqmd-349719_H/2
 Running data/oqmd-349719_H/3
 

 

-
  Elapsed time: 55.7 seconds for data/oqmd-349719_H/3
+
  Elapsed time: 40.4 seconds for data/oqmd-349719_H/3
 Running data/oqmd-349719_NNH/0
 

 

-
  Elapsed time: 139.3 seconds for data/oqmd-349719_NNH/0
+
  Elapsed time: 137.6 seconds for data/oqmd-349719_NNH/0
 Running data/oqmd-349719_NNH/1
 

 

-
  Elapsed time: 139.6 seconds for data/oqmd-349719_NNH/1
+
  Elapsed time: 117.6 seconds for data/oqmd-349719_NNH/1
 Running data/oqmd-349719_NNH/2
 

 

-
  Elapsed time: 139.2 seconds for data/oqmd-349719_NNH/2
+
  Elapsed time: 134.6 seconds for data/oqmd-349719_NNH/2
 Running data/oqmd-349719_NNH/3
 

 

-
100%|██████████| 1/1 [11:56<00:00, 716.30s/it]
+
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-
100%|██████████| 1/1 [11:56<00:00, 716.31s/it]
+
100%|██████████| 1/1 [11:06<00:00, 666.64s/it]
 

 

-
  Elapsed time: 137.9 seconds for data/oqmd-349719_NNH/3
-Elapsed time: 716.3 seconds
+
  Elapsed time: 135.0 seconds for data/oqmd-349719_NNH/3
+Elapsed time: 666.6 seconds
 

 

 

@@ -1279,7 +1189,7 @@ 
Make parity plots for values obtained by ML v. reported in the paper

 

-../../_images/33e748c54c65bf2c62d880db6f712a27cf22f1a234bc72238947a7f83abc602c.png
+../../_images/aa0f94393b055271b577afa74863460b56e85787ad0daaaab7aaed93b90e85a5.png
 

 

 

@@ -1333,7 +1243,7 @@ 
Make figure 6b and compare to literature results
-../../_images/4c0a3eadc20e85c10fa416a87bd8a8e66ed2141f9d738463e7fc40ceaccf7418.png
+../../_images/f9b0bc9c18d7454baec238a7cfbd8239d5be193923cbfba2bd94d16060c45393.png
 

 

 
diff --git a/tutorials/OCP-introduction.html b/tutorials/OCP-introduction.html
index 77910e0a8..f901968ec 100644
--- a/tutorials/OCP-introduction.html
+++ b/tutorials/OCP-introduction.html
@@ -742,60 +742,60 @@ 
Calculating adsorption energies
-
/tmp/ipykernel_4664/3494085424.py:6: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/3494085424.py:6: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:46:25        1.213984        1.630879
+BFGS:    0 17:01:43        1.213986        1.630879
 

 

-
BFGS:    1 14:46:26        1.072815        0.906401
+
BFGS:    1 17:01:44        1.072815        0.906401
 

 

-
BFGS:    2 14:46:26        0.981515        0.639872
+
BFGS:    2 17:01:45        0.981516        0.639873
 

 

-
BFGS:    3 14:46:27        0.960242        0.689923
+
BFGS:    3 17:01:45        0.960242        0.689923
 

 

-
BFGS:    4 14:46:27        0.880960        0.556051
+
BFGS:    4 17:01:46        0.880962        0.556050
 

 

-
BFGS:    5 14:46:28        0.835473        0.376718
+
BFGS:    5 17:01:47        0.835474        0.376719
 

 

-
BFGS:    6 14:46:29        0.823638        0.422298
+
BFGS:    6 17:01:47        0.824778        0.422334
 

 

-
BFGS:    7 14:46:29        0.812701        0.515638
+
BFGS:    7 17:01:48        0.812524        0.515162
 

 

-
BFGS:    8 14:46:30        0.825993        0.889763
+
BFGS:    8 17:01:48        0.826220        0.891041
 

 

-
BFGS:    9 14:46:30        0.779470        0.354202
+
BFGS:    9 17:01:49        0.781009        0.355374
 

 

-
BFGS:   10 14:46:31        0.770608        0.201519
+
BFGS:   10 17:01:50        0.770455        0.201346
 

 

-
BFGS:   11 14:46:32        0.757500        0.122539
+
BFGS:   11 17:01:50        0.757452        0.121917
 

 

-
BFGS:   12 14:46:32        0.755185        0.112457
+
BFGS:   12 17:01:51        0.754984        0.111666
 

 

-
BFGS:   13 14:46:33        0.754083        0.104408
+
BFGS:   13 17:01:51        0.754269        0.103800
 

 

-
BFGS:   14 14:46:33        0.755089        0.086535
+
BFGS:   14 17:01:52        0.755027        0.086329
 

 

-
BFGS:   15 14:46:34        0.757412        0.048986
+
BFGS:   15 17:01:53        0.757097        0.049460
 

 

-
-2.2725877451896666
+
-2.2729030537605284
 

 

 

@@ -815,7 +815,7 @@ 
Calculating adsorption energies
-../_images/c138d78d11c7e14374028e10ca0934ab2696fbf6aa9d2b45d44bcffabf6080e2.png
+../_images/b82ea1738fba5c90b56c624f7c437d6122aebdef0d1d9f361a1986abbc441734.png
 

 

 
How did we do? We need a reference point. In the paper below, there is an atomic adsorption energy for O on Pt(111) of about -4.264 eV. This is for the reaction O + * -> O*. To convert this to the dissociative adsorption energy, we have to add the reaction:

@@ -920,27 +920,27 @@ 
Trends in adsorption energies across metals.
-
/tmp/ipykernel_4664/2476004300.py:10: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/2476004300.py:10: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:46:35        0.720971        0.217973
+BFGS:    0 17:01:54        0.720971        0.217973
 

 

-
BFGS:    1 14:46:36        0.717581        0.182150
+
BFGS:    1 17:01:54        0.717582        0.182150
 

 

-
BFGS:    2 14:46:37        0.707524        0.067373
+
BFGS:    2 17:01:55        0.707524        0.067377
 

 

-
BFGS:    3 14:46:37        0.705303        0.062101
+
BFGS:    3 17:01:56        0.705305        0.062093
 

 

-
BFGS:    4 14:46:37        0.701209        0.049769
+
BFGS:    4 17:01:56        0.701209        0.049767
 

 

-
-4.908790514469146
+
-4.908790872097015
 

 

 

@@ -1003,14 +1003,14 @@ 
Site correlations
  0%|          | 0/1 [00:00<?, ?it/s]
 

 

-
/tmp/ipykernel_4664/1169188772.py:27: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/1169188772.py:27: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

-
100%|██████████| 1/1 [00:02<00:00,  2.93s/it]
+
100%|██████████| 1/1 [00:02<00:00,  2.94s/it]
 

 

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+
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@@ -1034,10 +1034,10 @@ 
Site correlations
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+
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+
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@@ -1046,10 +1046,10 @@ 
Site correlations
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100%|██████████| 1/1 [00:03<00:00,  3.42s/it]
+
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+
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@@ -1061,10 +1061,10 @@ 
Site correlations
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100%|██████████| 1/1 [00:02<00:00,  2.89s/it]
+
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+
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@@ -1073,10 +1073,10 @@ 
Site correlations
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100%|██████████| 1/1 [00:03<00:00,  3.39s/it]
+
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100%|██████████| 1/1 [00:03<00:00,  3.39s/it]
+
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@@ -1088,10 +1088,10 @@ 
Site correlations
  0%|          | 0/1 [00:00<?, ?it/s]
 

 

-
100%|██████████| 1/1 [00:02<00:00,  2.42s/it]
+
100%|██████████| 1/1 [00:02<00:00,  2.48s/it]
 

 

-
100%|██████████| 1/1 [00:02<00:00,  2.42s/it]
+
100%|██████████| 1/1 [00:02<00:00,  2.49s/it]
 

 

 

@@ -1100,10 +1100,10 @@ 
Site correlations
  0%|          | 0/1 [00:00<?, ?it/s]
 

 

-
100%|██████████| 1/1 [00:01<00:00,  1.46s/it]
+
100%|██████████| 1/1 [00:01<00:00,  1.49s/it]
 

 

-
100%|██████████| 1/1 [00:01<00:00,  1.46s/it]
+
100%|██████████| 1/1 [00:01<00:00,  1.49s/it]
 

 

 

@@ -1115,10 +1115,10 @@ 
Site correlations
  0%|          | 0/1 [00:00<?, ?it/s]
 

 

-
100%|██████████| 1/1 [00:00<00:00,  2.06it/s]
+
100%|██████████| 1/1 [00:00<00:00,  1.91it/s]
 

 

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100%|██████████| 1/1 [00:00<00:00,  2.05it/s]
+
100%|██████████| 1/1 [00:00<00:00,  1.90it/s]
 

 

 

@@ -1127,10 +1127,10 @@ 
Site correlations
  0%|          | 0/1 [00:00<?, ?it/s]
 

 

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100%|██████████| 1/1 [00:00<00:00,  2.05it/s]
+
100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
 

 

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100%|██████████| 1/1 [00:00<00:00,  2.05it/s]
+
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@@ -1142,10 +1142,10 @@ 
Site correlations
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100%|██████████| 1/1 [00:01<00:00,  1.47s/it]
+
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+
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@@ -1154,16 +1154,16 @@ 
Site correlations
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100%|██████████| 1/1 [00:00<00:00,  1.04it/s]
+
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100%|██████████| 1/1 [00:00<00:00,  1.04it/s]
+
100%|██████████| 1/1 [00:01<00:00,  1.02s/it]
 

 

 

 

 

-
'Elapsed time = 25.313016176223755 seconds'
+
'Elapsed time = 26.161882400512695 seconds'
 

 

 

@@ -1234,7 +1234,7 @@ 
Effects of number of layers
-
/tmp/ipykernel_4664/4214609233.py:5: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/4214609233.py:5: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

@@ -1282,7 +1282,7 @@ 
Effects of relaxation
 

 

-
/tmp/ipykernel_4664/2738246227.py:9: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/2738246227.py:9: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

@@ -1327,7 +1327,7 @@ 
Unit cell size
-
/tmp/ipykernel_4664/1073633840.py:7: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4503/1073633840.py:7: DeprecationWarning: Please use atoms.calc = calc
   slab.set_calculator(calc)
 

 

diff --git a/tutorials/adsorbml_walkthrough.html b/tutorials/adsorbml_walkthrough.html
index ae684bf4a..ea5f39645 100644
--- a/tutorials/adsorbml_walkthrough.html
+++ b/tutorials/adsorbml_walkthrough.html
@@ -732,509 +732,527 @@ 
Run ML relaxations:
      Step     Time          Energy          fmax
-BFGS:    0 14:50:33       -0.434045        1.876343
+BFGS:    0 17:05:54       -0.235652        1.103761
 

 

-
BFGS:    1 14:50:36       -0.432490        2.292801
+
BFGS:    1 17:05:57       -0.266137        1.496283
 

 

-
BFGS:    2 14:50:38       -0.464647        0.735988
+
BFGS:    2 17:06:00       -0.362913        1.821989
 

 

-
BFGS:    3 14:50:41       -0.484850        0.691235
+
BFGS:    3 17:06:03       -0.439787        1.462454
 

 

-
BFGS:    4 14:50:44       -0.524902        1.179055
+
BFGS:    4 17:06:06       -0.476487        0.642766
 

 

-
BFGS:    5 14:50:46       -0.551819        0.548770
+
BFGS:    5 17:06:09       -0.494250        0.295910
 

 

-
BFGS:    6 14:50:49       -0.554777        0.183322
+
BFGS:    6 17:06:12       -0.500390        0.173732
 

 

-
BFGS:    7 14:50:52       -0.555021        0.181293
+
BFGS:    7 17:06:15       -0.501494        0.161376
 

 

-
BFGS:    8 14:50:54       -0.554881        0.276152
+
BFGS:    8 17:06:17       -0.516526        0.234461
 

 

-
BFGS:    9 14:50:57       -0.557610        0.274996
+
BFGS:    9 17:06:20       -0.519665        0.193556
 

 

-
BFGS:   10 14:50:59       -0.561256        0.175103
+
BFGS:   10 17:06:23       -0.521455        0.093788
 

 

-
BFGS:   11 14:51:02       -0.562532        0.070345
+
BFGS:   11 17:06:26       -0.523525        0.209819
 

 

-
BFGS:   12 14:51:05       -0.563194        0.104535
+
BFGS:   12 17:06:29       -0.526306        0.308883
 

 

-
BFGS:   13 14:51:07       -0.564646        0.198865
+
BFGS:   13 17:06:32       -0.528410        0.274371
 

 

-
BFGS:   14 14:51:10       -0.565199        0.214102
+
BFGS:   14 17:06:35       -0.528541        0.205441
 

 

-
BFGS:   15 14:51:13       -0.565884        0.129744
+
BFGS:   15 17:06:37       -0.528008        0.095832
 

 

-
BFGS:   16 14:51:15       -0.566448        0.090119
+
BFGS:   16 17:06:40       -0.528599        0.069097
 

 

-
BFGS:   17 14:51:18       -0.567316        0.033248
+
BFGS:   17 17:06:43       -0.531778        0.166889
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:51:20       -0.308287        1.370556
+
BFGS:   18 17:06:46       -0.533354        0.133099
 

 

-
BFGS:    1 14:51:23       -0.320614        1.622943
+
BFGS:   19 17:06:49       -0.535810        0.024699
 

 

-
BFGS:    2 14:51:26       -0.356598        1.137395
+
      Step     Time          Energy          fmax
+BFGS:    0 17:06:52       -0.460799        1.845155
 

 

-
BFGS:    3 14:51:28       -0.487838        0.816723
+
BFGS:    1 17:06:55       -0.458687        2.265170
 

 

-
BFGS:    4 14:51:31       -0.494663        0.237197
+
BFGS:    2 17:06:57       -0.488440        0.674833
 

 

-
BFGS:    5 14:51:33       -0.498462        0.183613
+
BFGS:    3 17:07:00       -0.505889        0.614540
 

 

-
BFGS:    6 14:51:36       -0.509730        0.188491
+
BFGS:    4 17:07:03       -0.536232        1.160239
 

 

-
BFGS:    7 14:51:39       -0.513349        0.152629
+
BFGS:    5 17:07:06       -0.555601        0.726879
 

 

-
BFGS:    8 14:51:41       -0.517116        0.091037
+
BFGS:    6 17:07:09       -0.560924        0.208073
 

 

-
BFGS:    9 14:51:44       -0.517656        0.093658
+
BFGS:    7 17:07:11       -0.562171        0.074853
 

 

-
BFGS:   10 14:51:47       -0.519498        0.112155
+
BFGS:    8 17:07:14       -0.564436        0.139862
 

 

-
BFGS:   11 14:51:49       -0.522195        0.080045
+
BFGS:    9 17:07:17       -0.563794        0.153849
 

 

-
BFGS:   12 14:51:52       -0.524058        0.057600
+
BFGS:   10 17:07:20       -0.564959        0.097076
 

 

-
BFGS:   13 14:51:54       -0.524077        0.042604
+
BFGS:   11 17:07:23       -0.565432        0.028982
 

 

 
      Step     Time          Energy          fmax
-BFGS:    0 14:51:57       -0.233589        1.100674
+BFGS:    0 17:07:26       -0.454595        1.870581
 

 

-
BFGS:    1 14:52:00       -0.264950        1.496396
+
BFGS:    1 17:07:28       -0.451744        2.289944
 

 

-
BFGS:    2 14:52:02       -0.362048        1.818655
+
BFGS:    2 17:07:31       -0.483226        0.693375
 

 

-
BFGS:    3 14:52:05       -0.438750        1.471447
+
BFGS:    3 17:07:34       -0.500765        0.629519
 

 

-
BFGS:    4 14:52:08       -0.475506        0.650425
+
BFGS:    4 17:07:37       -0.535400        1.136181
 

 

-
BFGS:    5 14:52:10       -0.493818        0.299185
+
BFGS:    5 17:07:40       -0.555887        0.645818
 

 

-
BFGS:    6 14:52:13       -0.500170        0.178635
+
BFGS:    6 17:07:43       -0.559387        0.175901
 

 

-
BFGS:    7 14:52:16       -0.501162        0.165988
+
BFGS:    7 17:07:46       -0.559676        0.110681
 

 

-
BFGS:    8 14:52:18       -0.515941        0.234457
+
BFGS:    8 17:07:48       -0.559745        0.196557
 

 

-
BFGS:    9 14:52:21       -0.519230        0.198493
+
BFGS:    9 17:07:51       -0.560626        0.200869
 

 

-
BFGS:   10 14:52:23       -0.521026        0.090961
+
BFGS:   10 17:07:54       -0.562992        0.125742
 

 

-
BFGS:   11 14:52:26       -0.522713        0.197972
+
BFGS:   11 17:07:57       -0.564787        0.050646
 

 

-
BFGS:   12 14:52:29       -0.525443        0.308587
+
BFGS:   12 17:08:00       -0.564891        0.041084
 

 

-
BFGS:   13 14:52:32       -0.527565        0.282008
+
      Step     Time          Energy          fmax
+BFGS:    0 17:08:02       -0.310796        1.341757
 

 

-
BFGS:   14 14:52:34       -0.528322        0.215016
+
BFGS:    1 17:08:05       -0.320901        1.607917
 

 

-
BFGS:   15 14:52:37       -0.527808        0.100678
+
BFGS:    2 17:08:08       -0.358334        1.140967
 

 

-
BFGS:   16 14:52:39       -0.528028        0.060785
+
BFGS:    3 17:08:11       -0.484380        0.790749
 

 

-
BFGS:   17 14:52:42       -0.531426        0.158212
+
BFGS:    4 17:08:14       -0.493668        0.257245
 

 

-
BFGS:   18 14:52:45       -0.532836        0.130982
+
BFGS:    5 17:08:16       -0.495713        0.190507
 

 

-
BFGS:   19 14:52:47       -0.535812        0.027128
+
BFGS:    6 17:08:19       -0.503721        0.233187
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:52:50       -0.426613        1.861851
+
BFGS:    7 17:08:22       -0.507672        0.245639
 

 

-
BFGS:    1 14:52:52       -0.425644        2.277712
+
BFGS:    8 17:08:25       -0.512372        0.127760
 

 

-
BFGS:    2 14:52:55       -0.458086        0.745481
+
BFGS:    9 17:08:28       -0.513860        0.110742
 

 

-
BFGS:    3 14:52:58       -0.478327        0.711408
+
BFGS:   10 17:08:30       -0.515886        0.162336
 

 

-
BFGS:    4 14:53:00       -0.520039        1.224011
+
BFGS:   11 17:08:33       -0.517828        0.170266
 

 

-
BFGS:    5 14:53:03       -0.548619        0.572794
+
BFGS:   12 17:08:36       -0.519232        0.105665
 

 

-
BFGS:    6 14:53:05       -0.551888        0.192441
+
BFGS:   13 17:08:39       -0.519530        0.072174
 

 

-
BFGS:    7 14:53:08       -0.552721        0.178404
+
BFGS:   14 17:08:42       -0.519792        0.061863
 

 

-
BFGS:    8 14:53:11       -0.552917        0.278055
+
BFGS:   15 17:08:44       -0.519929        0.064448
 

 

-
BFGS:    9 14:53:13       -0.554997        0.297114
+
BFGS:   16 17:08:47       -0.520016        0.067324
 

 

-
BFGS:   10 14:53:16       -0.559577        0.206489
+
BFGS:   17 17:08:50       -0.521433        0.053114
 

 

-
BFGS:   11 14:53:19       -0.561349        0.084311
+
BFGS:   18 17:08:53       -0.522263        0.046959
 

 

-
BFGS:   12 14:53:21       -0.562092        0.112185
+
      Step     Time          Energy          fmax
+BFGS:    0 17:08:56       -0.206615        1.024930
 

 

-
BFGS:   13 14:53:24       -0.562643        0.209506
+
BFGS:    1 17:08:59       -0.239334        1.477607
 

 

-
BFGS:   14 14:53:26       -0.563725        0.218124
+
BFGS:    2 17:09:01       -0.335659        1.796537
 

 

-
BFGS:   15 14:53:29       -0.564785        0.145476
+
BFGS:    3 17:09:04       -0.413160        1.637522
 

 

-
BFGS:   16 14:53:32       -0.565451        0.105704
+
BFGS:    4 17:09:07       -0.455931        0.814910
 

 

-
BFGS:   17 14:53:34       -0.566211        0.030433
+
BFGS:    5 17:09:10       -0.477420        0.386822
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:53:37       -0.216614        1.035457
+
BFGS:    6 17:09:13       -0.486010        0.295870
 

 

-
BFGS:    1 14:53:39       -0.247354        1.154556
+
BFGS:    7 17:09:16       -0.488503        0.266534
 

 

-
BFGS:    2 14:53:42       -0.426440        2.009409
+
BFGS:    8 17:09:18       -0.508304        0.525401
 

 

-
BFGS:    3 14:53:45       -0.310458        2.670408
+
BFGS:    9 17:09:21       -0.510905        0.191454
 

 

-
BFGS:    4 14:53:47       -0.464650        0.630521
+
BFGS:   10 17:09:24       -0.513397        0.117505
 

 

-
BFGS:    5 14:53:50       -0.473249        0.332306
+
BFGS:   11 17:09:27       -0.515128        0.171320
 

 

-
BFGS:    6 14:53:53       -0.481078        0.250549
+
BFGS:   12 17:09:30       -0.516907        0.217548
 

 

-
BFGS:    7 14:53:55       -0.483275        0.252528
+
BFGS:   13 17:09:33       -0.519994        0.259712
 

 

-
BFGS:    8 14:53:58       -0.496505        0.276092
+
BFGS:   14 17:09:35       -0.523378        0.248275
 

 

-
BFGS:    9 14:54:00       -0.497065        0.161574
+
BFGS:   15 17:09:38       -0.526813        0.201452
 

 

-
BFGS:   10 14:54:03       -0.498100        0.119208
+
BFGS:   16 17:09:41       -0.527185        0.078640
 

 

-
BFGS:   11 14:54:06       -0.499339        0.217968
+
BFGS:   17 17:09:44       -0.527436        0.068455
 

 

-
BFGS:   12 14:54:08       -0.501554        0.298537
+
BFGS:   18 17:09:47       -0.527699        0.092253
 

 

-
BFGS:   13 14:54:11       -0.504334        0.279552
+
BFGS:   19 17:09:49       -0.529165        0.080691
 

 

-
BFGS:   14 14:54:14       -0.506634        0.215069
+
BFGS:   20 17:09:52       -0.530396        0.038558
 

 

-
BFGS:   15 14:54:16       -0.508143        0.094620
+
      Step     Time          Energy          fmax
+BFGS:    0 17:09:55       -0.216121        1.041792
 

 

-
BFGS:   16 14:54:19       -0.508474        0.114219
+
BFGS:    1 17:09:58       -0.247922        1.332999
 

 

-
BFGS:   17 14:54:22       -0.509799        0.209296
+
BFGS:    2 17:10:01       -0.381626        2.007481
 

 

-
BFGS:   18 14:54:24       -0.513084        0.216512
+
BFGS:    3 17:10:04       -0.349284        2.382707
 

 

-
BFGS:   19 14:54:27       -0.515703        0.115601
+
BFGS:    4 17:10:06       -0.460992        0.857937
 

 

-
BFGS:   20 14:54:29       -0.517310        0.033437
+
BFGS:    5 17:10:09       -0.479584        0.435720
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:54:32       -0.231223        1.097216
+
BFGS:    6 17:10:12       -0.489841        0.277698
 

 

-
BFGS:    1 14:54:35       -0.262252        1.451755
+
BFGS:    7 17:10:15       -0.491317        0.229332
 

 

-
BFGS:    2 14:54:37       -0.367091        1.888308
+
BFGS:    8 17:10:18       -0.503025        0.141059
 

 

-
BFGS:    3 14:54:40       -0.424873        1.621224
+
BFGS:    9 17:10:21       -0.507415        0.195501
 

 

-
BFGS:    4 14:54:43       -0.472109        0.695738
+
BFGS:   10 17:10:24       -0.508931        0.185297
 

 

-
BFGS:    5 14:54:45       -0.490931        0.325708
+
BFGS:   11 17:10:27       -0.510300        0.074861
 

 

-
BFGS:    6 14:54:48       -0.498128        0.186885
+
BFGS:   12 17:10:30       -0.512716        0.215101
 

 

-
BFGS:    7 14:54:50       -0.499195        0.167867
+
BFGS:   13 17:10:32       -0.514805        0.286763
 

 

-
BFGS:    8 14:54:53       -0.512800        0.215767
+
BFGS:   14 17:10:35       -0.516986        0.291721
 

 

-
BFGS:    9 14:54:56       -0.516375        0.198368
+
BFGS:   15 17:10:38       -0.519380        0.246879
 

 

-
BFGS:   10 14:54:58       -0.518111        0.087863
+
BFGS:   16 17:10:41       -0.519770        0.131241
 

 

-
BFGS:   11 14:55:01       -0.519756        0.177841
+
BFGS:   17 17:10:44       -0.520189        0.127298
 

 

-
BFGS:   12 14:55:04       -0.522546        0.294174
+
BFGS:   18 17:10:47       -0.521032        0.179480
 

 

-
BFGS:   13 14:55:06       -0.524341        0.283405
+
BFGS:   19 17:10:49       -0.525170        0.167852
 

 

-
BFGS:   14 14:55:09       -0.525288        0.211950
+
BFGS:   20 17:10:52       -0.527836        0.076206
 

 

-
BFGS:   15 14:55:11       -0.525084        0.102470
+
BFGS:   21 17:10:55       -0.529021        0.018719
 

 

-
BFGS:   16 14:55:14       -0.525783        0.061891
+
      Step     Time          Energy          fmax
+BFGS:    0 17:10:58       -0.294813        1.321209
 

 

-
BFGS:   17 14:55:17       -0.528809        0.171496
+
BFGS:    1 17:11:01       -0.306751        1.630593
 

 

-
BFGS:   18 14:55:19       -0.530353        0.146184
+
BFGS:    2 17:11:04       -0.340067        1.205568
 

 

-
BFGS:   19 14:55:22       -0.533057        0.040351
+
BFGS:    3 17:11:06       -0.427209        1.362099
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:55:24       -0.289749        1.189858
+
BFGS:    4 17:11:09       -0.461885        0.506380
 

 

-
BFGS:    1 14:55:27       -0.303529        1.470310
+
BFGS:    5 17:11:12       -0.472558        0.299657
 

 

-
BFGS:    2 14:55:30       -0.344054        1.317918
+
BFGS:    6 17:11:15       -0.479252        0.395381
 

 

-
BFGS:    3 14:55:32       -0.343532        2.156508
+
BFGS:    7 17:11:18       -0.486213        0.445347
 

 

-
BFGS:    4 14:55:35       -0.449672        0.618212
+
BFGS:    8 17:11:21       -0.508453        0.560499
 

 

-
BFGS:    5 14:55:37       -0.465934        0.319246
+
BFGS:    9 17:11:23       -0.522054        0.451219
 

 

-
BFGS:    6 14:55:40       -0.474551        0.362688
+
BFGS:   10 17:11:26       -0.533850        0.235751
 

 

-
BFGS:    7 14:55:43       -0.477363        0.362723
+
BFGS:   11 17:11:29       -0.538935        0.291290
 

 

-
BFGS:    8 14:55:45       -0.506876        0.230836
+
BFGS:   12 17:11:32       -0.546674        0.286936
 

 

-
BFGS:    9 14:55:48       -0.510398        0.164068
+
BFGS:   13 17:11:35       -0.553613        0.243172
 

 

-
BFGS:   10 14:55:50       -0.515258        0.245246
+
BFGS:   14 17:11:37       -0.557394        0.137376
 

 

-
BFGS:   11 14:55:53       -0.521632        0.306852
+
BFGS:   15 17:11:40       -0.557492        0.145011
 

 

-
BFGS:   12 14:55:56       -0.529798        0.248002
+
BFGS:   16 17:11:43       -0.557431        0.120322
 

 

-
BFGS:   13 14:55:59       -0.533035        0.178062
+
BFGS:   17 17:11:46       -0.559263        0.109065
 

 

-
BFGS:   14 14:56:01       -0.535859        0.176910
+
BFGS:   18 17:11:49       -0.559878        0.079431
 

 

-
BFGS:   15 14:56:04       -0.536725        0.179931
+
BFGS:   19 17:11:52       -0.562454        0.078072
 

 

-
BFGS:   16 14:56:06       -0.537177        0.171981
+
BFGS:   20 17:11:54       -0.562469        0.047208
 

 

-
BFGS:   17 14:56:09       -0.537564        0.229277
+
      Step     Time          Energy          fmax
+BFGS:    0 17:11:57       -0.191666        0.816003
 

 

-
BFGS:   18 14:56:12       -0.539703        0.166756
+
BFGS:    1 17:12:00       -0.213628        0.792215
 

 

-
BFGS:   19 14:56:14       -0.541529        0.099435
+
BFGS:    2 17:12:03       -0.376765        2.133192
 

 

-
BFGS:   20 14:56:17       -0.542201        0.100529
+
BFGS:    3 17:12:06       -0.394693        1.077923
 

 

-
BFGS:   21 14:56:19       -0.543756        0.137052
+
BFGS:    4 17:12:09       -0.421634        0.421195
 

 

-
BFGS:   22 14:56:22       -0.545730        0.204109
+
BFGS:    5 17:12:11       -0.431416        0.442040
 

 

-
BFGS:   23 14:56:25       -0.547644        0.156100
+
BFGS:    6 17:12:14       -0.437063        0.418186
 

 

-
BFGS:   24 14:56:27       -0.549652        0.164689
+
BFGS:    7 17:12:17       -0.465893        1.003935
 

 

-
BFGS:   25 14:56:30       -0.550832        0.097445
+
BFGS:    8 17:12:20       -0.474805        0.234654
 

 

-
BFGS:   26 14:56:32       -0.551969        0.086518
+
BFGS:    9 17:12:23       -0.475837        0.098806
 

 

-
BFGS:   27 14:56:35       -0.552727        0.108750
+
BFGS:   10 17:12:26       -0.476423        0.137043
 

 

-
BFGS:   28 14:56:38       -0.557108        0.100960
+
BFGS:   11 17:12:28       -0.477463        0.097260
 

 

-
BFGS:   29 14:56:40       -0.560345        0.072570
+
BFGS:   12 17:12:31       -0.480521        0.106807
 

 

-
BFGS:   30 14:56:43       -0.561664        0.069722
+
BFGS:   13 17:12:34       -0.482542        0.110958
 

 

-
BFGS:   31 14:56:46       -0.562052        0.058983
+
BFGS:   14 17:12:37       -0.484374        0.072014
 

 

-
BFGS:   32 14:56:48       -0.562995        0.077771
+
BFGS:   15 17:12:40       -0.485466        0.059318
 

 

-
BFGS:   33 14:56:51       -0.564787        0.076415
+
BFGS:   16 17:12:43       -0.485863        0.094789
 

 

-
BFGS:   34 14:56:53       -0.566557        0.059309
+
BFGS:   17 17:12:46       -0.486856        0.130698
 

 

-
BFGS:   35 14:56:56       -0.567388        0.040934
+
BFGS:   18 17:12:49       -0.487448        0.111919
 

 

-
      Step     Time          Energy          fmax
-BFGS:    0 14:56:58       -0.265663        1.118231
+
BFGS:   19 17:12:52       -0.488177        0.060268
+

+

+
BFGS:   20 17:12:54       -0.488755        0.060405
+

+

+
BFGS:   21 17:12:57       -0.489146        0.078366
 

 

-
BFGS:    1 14:57:01       -0.278597        1.353561
+
BFGS:   22 17:13:00       -0.489443        0.108700
 

 

-
BFGS:    2 14:57:04       -0.322397        1.360928
+
BFGS:   23 17:13:03       -0.489552        0.138543
 

 

-
BFGS:    3 14:57:06       -0.304625        3.276865
+
BFGS:   24 17:13:06       -0.490736        0.128628
 

 

-
BFGS:    4 14:57:09       -0.448378        0.716737
+
BFGS:   25 17:13:09       -0.492357        0.059135
 

 

-
BFGS:    5 14:57:12       -0.468337        0.278497
+
BFGS:   26 17:13:11       -0.493139        0.084882
 

 

-
BFGS:    6 14:57:14       -0.478023        0.385621
+
BFGS:   27 17:13:14       -0.493876        0.095745
 

 

-
BFGS:    7 14:57:17       -0.480715        0.354220
+
BFGS:   28 17:13:17       -0.494786        0.114963
 

 

-
BFGS:    8 14:57:20       -0.498207        0.162403
+
BFGS:   29 17:13:20       -0.497580        0.101895
 

 

-
BFGS:    9 14:57:22       -0.499696        0.150275
+
BFGS:   30 17:13:23       -0.500184        0.155295
 

 

-
BFGS:   10 14:57:25       -0.506174        0.205667
+
BFGS:   31 17:13:26       -0.501808        0.090314
 

 

-
BFGS:   11 14:57:27       -0.510518        0.231858
+
BFGS:   32 17:13:29       -0.502609        0.144097
 

 

-
BFGS:   12 14:57:30       -0.513796        0.167350
+
BFGS:   33 17:13:32       -0.504268        0.178550
 

 

-
BFGS:   13 14:57:33       -0.514851        0.097503
+
BFGS:   34 17:13:35       -0.508122        0.312106
 

 

-
BFGS:   14 14:57:35       -0.515062        0.106068
+
BFGS:   35 17:13:38       -0.511063        0.383742
 

 

-
BFGS:   15 14:57:38       -0.515366        0.112009
+
BFGS:   36 17:13:40       -0.516837        0.170124
 

 

-
BFGS:   16 14:57:40       -0.515500        0.118600
+
BFGS:   37 17:13:43       -0.515030        0.431350
 

 

-
BFGS:   17 14:57:43       -0.516888        0.092608
+
BFGS:   38 17:13:46       -0.521811        0.136103
 

 

-
BFGS:   18 14:57:45       -0.517796        0.048217
+
BFGS:   39 17:13:49       -0.523959        0.088556
+

+

+
BFGS:   40 17:13:52       -0.524551        0.116880
+

+

+
BFGS:   41 17:13:55       -0.527259        0.105810
+

+

+
BFGS:   42 17:13:58       -0.530594        0.114091
+

+

+
BFGS:   43 17:14:00       -0.532879        0.030570
 

 

 

@@ -1311,58 +1329,58 @@ 
Parse the trajectories and post-process
-
The lowest 5 energies are: [-0.567 -0.536 -0.524]
+
The lowest 5 energies are: [-0.565 -0.536 -0.522]
 

 

 

@@ -1509,27 +1527,27 @@ 
(Optional) Deduplicate structures
-
/tmp/ipykernel_4772/147314410.py:15: DeprecationWarning: Please use atoms.calc = calc
+
/tmp/ipykernel_4685/147314410.py:15: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 

 

diff --git a/tutorials/advanced/fine-tuning-in-python.html b/tutorials/advanced/fine-tuning-in-python.html
index 2a3b04c02..72559b8a8 100644
--- a/tutorials/advanced/fine-tuning-in-python.html
+++ b/tutorials/advanced/fine-tuning-in-python.html
@@ -679,26 +679,26 @@ 
Fine-tuning with Python
 

 
id|age|user  |formula|calculator| energy|natoms| fmax|pbc| volume|charge|   mass
- 1|48m|runner|Sn2O4  |unknown   |-41.359|     6|0.045|TTT| 64.258| 0.000|301.416
- 2|48m|runner|Sn2O4  |unknown   |-41.853|     6|0.025|TTT| 66.526| 0.000|301.416
- 3|48m|runner|Sn2O4  |unknown   |-42.199|     6|0.010|TTT| 68.794| 0.000|301.416
- 4|48m|runner|Sn2O4  |unknown   |-42.419|     6|0.006|TTT| 71.062| 0.000|301.416
- 5|48m|runner|Sn2O4  |unknown   |-42.534|     6|0.011|TTT| 73.330| 0.000|301.416
- 6|48m|runner|Sn2O4  |unknown   |-42.562|     6|0.029|TTT| 75.598| 0.000|301.416
- 7|48m|runner|Sn2O4  |unknown   |-42.518|     6|0.033|TTT| 77.866| 0.000|301.416
- 8|48m|runner|Sn2O4  |unknown   |-42.415|     6|0.010|TTT| 80.134| 0.000|301.416
- 9|48m|runner|Sn2O4  |unknown   |-42.266|     6|0.006|TTT| 82.402| 0.000|301.416
-10|48m|runner|Sn2O4  |unknown   |-42.083|     6|0.017|TTT| 84.670| 0.000|301.416
-11|48m|runner|Sn4O8  |unknown   |-81.424|    12|0.012|TTT|117.473| 0.000|602.832
-12|48m|runner|Sn4O8  |unknown   |-82.437|    12|0.005|TTT|121.620| 0.000|602.832
-13|48m|runner|Sn4O8  |unknown   |-83.147|    12|0.015|TTT|125.766| 0.000|602.832
-14|48m|runner|Sn4O8  |unknown   |-83.599|    12|0.047|TTT|129.912| 0.000|602.832
-15|48m|runner|Sn4O8  |unknown   |-83.831|    12|0.081|TTT|134.058| 0.000|602.832
-16|48m|runner|Sn4O8  |unknown   |-83.898|    12|0.001|TTT|138.204| 0.000|602.832
-17|48m|runner|Sn4O8  |unknown   |-83.805|    12|0.001|TTT|142.350| 0.000|602.832
-18|48m|runner|Sn4O8  |unknown   |-83.586|    12|0.002|TTT|146.496| 0.000|602.832
-19|48m|runner|Sn4O8  |unknown   |-83.262|    12|0.002|TTT|150.642| 0.000|602.832
-20|48m|runner|Sn4O8  |unknown   |-82.851|    12|0.013|TTT|154.788| 0.000|602.832
+ 1|47m|runner|Sn2O4  |unknown   |-41.359|     6|0.045|TTT| 64.258| 0.000|301.416
+ 2|47m|runner|Sn2O4  |unknown   |-41.853|     6|0.025|TTT| 66.526| 0.000|301.416
+ 3|47m|runner|Sn2O4  |unknown   |-42.199|     6|0.010|TTT| 68.794| 0.000|301.416
+ 4|47m|runner|Sn2O4  |unknown   |-42.419|     6|0.006|TTT| 71.062| 0.000|301.416
+ 5|47m|runner|Sn2O4  |unknown   |-42.534|     6|0.011|TTT| 73.330| 0.000|301.416
+ 6|47m|runner|Sn2O4  |unknown   |-42.562|     6|0.029|TTT| 75.598| 0.000|301.416
+ 7|47m|runner|Sn2O4  |unknown   |-42.518|     6|0.033|TTT| 77.866| 0.000|301.416
+ 8|47m|runner|Sn2O4  |unknown   |-42.415|     6|0.010|TTT| 80.134| 0.000|301.416
+ 9|47m|runner|Sn2O4  |unknown   |-42.266|     6|0.006|TTT| 82.402| 0.000|301.416
+10|47m|runner|Sn2O4  |unknown   |-42.083|     6|0.017|TTT| 84.670| 0.000|301.416
+11|47m|runner|Sn4O8  |unknown   |-81.424|    12|0.012|TTT|117.473| 0.000|602.832
+12|47m|runner|Sn4O8  |unknown   |-82.437|    12|0.005|TTT|121.620| 0.000|602.832
+13|47m|runner|Sn4O8  |unknown   |-83.147|    12|0.015|TTT|125.766| 0.000|602.832
+14|47m|runner|Sn4O8  |unknown   |-83.599|    12|0.047|TTT|129.912| 0.000|602.832
+15|47m|runner|Sn4O8  |unknown   |-83.831|    12|0.081|TTT|134.058| 0.000|602.832
+16|47m|runner|Sn4O8  |unknown   |-83.898|    12|0.001|TTT|138.204| 0.000|602.832
+17|47m|runner|Sn4O8  |unknown   |-83.805|    12|0.001|TTT|142.350| 0.000|602.832
+18|47m|runner|Sn4O8  |unknown   |-83.586|    12|0.002|TTT|146.496| 0.000|602.832
+19|47m|runner|Sn4O8  |unknown   |-83.262|    12|0.002|TTT|150.642| 0.000|602.832
+20|47m|runner|Sn4O8  |unknown   |-82.851|    12|0.013|TTT|154.788| 0.000|602.832
 Rows: 295 (showing first 20)
 

 

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@@ -1162,28 +1162,28 @@ 
Run the training task
 

 

-
2024-07-09 14:59:21 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
-2024-07-09 14:59:21 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
-2024-07-09 14:59:23 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated.
-2024-07-09 14:59:24 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
-2024-07-09 14:59:25 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
-2024-07-09 14:59:25 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
-2024-07-09 14:59:27 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated.
-2024-07-09 14:59:27 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
-2024-07-09 14:59:27 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
-2024-07-09 14:59:29 (WARNING): log_summary for Tensorboard not supported
-

-

-
2024-07-09 15:01:15 (INFO): energy_mae: 4.4741, forcesx_mae: 0.0270, forcesy_mae: 0.0292, forcesz_mae: 0.0332, forces_mae: 0.0298, forces_cosine_similarity: -0.0277, forces_magnitude_error: 0.0421, energy_forces_within_threshold: 0.0000, loss: 4.5647, epoch: 0.5085
-2024-07-09 15:01:40 (INFO): energy_mae: 3.80e+00, forcesx_mae: 3.12e-02, forcesy_mae: 2.71e-02, forcesz_mae: 3.31e-02, forces_mae: 3.05e-02, forces_cosine_similarity: -1.19e-01, forces_magnitude_error: 3.99e-02, energy_forces_within_threshold: 0.00e+00, loss: 3.86e+00, lr: 5.00e-04, epoch: 6.78e-01, step: 4.00e+01
-2024-07-09 15:01:42 (INFO): Evaluating on val.
-2024-07-09 15:01:49 (INFO): energy_mae: 1.3243, forcesx_mae: 0.0155, forcesy_mae: 0.0188, forcesz_mae: 0.0151, forces_mae: 0.0165, forces_cosine_similarity: 0.1137, forces_magnitude_error: 0.0201, energy_forces_within_threshold: 0.0000, loss: 1.3485, epoch: 0.6780
-2024-07-09 15:01:50 (INFO): Predicting on test.
-2024-07-09 15:01:56 (INFO): Writing results to ./results/2024-07-09-15-00-16/ocp_predictions.npz
-2024-07-09 15:02:16 (INFO): energy_mae: 3.84e+00, forcesx_mae: 2.49e-02, forcesy_mae: 2.48e-02, forcesz_mae: 1.99e-02, forces_mae: 2.32e-02, forces_cosine_similarity: -7.56e-02, forces_magnitude_error: 3.17e-02, energy_forces_within_threshold: 2.50e-02, loss: 3.88e+00, lr: 5.00e-04, epoch: 8.47e-01, step: 5.00e+01
-2024-07-09 15:02:18 (INFO): Evaluating on val.
-2024-07-09 15:02:26 (INFO): energy_mae: 5.0580, forcesx_mae: 0.0243, forcesy_mae: 0.0286, forcesz_mae: 0.0282, forces_mae: 0.0270, forces_cosine_similarity: -0.0074, forces_magnitude_error: 0.0382, energy_forces_within_threshold: 0.0000, loss: 5.0424, epoch: 0.8475
-2024-07-09 15:02:45 (INFO): Total time taken: 195.57529306411743
+
2024-07-10 17:15:37 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+2024-07-10 17:15:37 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
+2024-07-10 17:15:39 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated.
+2024-07-10 17:15:40 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
+2024-07-10 17:15:41 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+2024-07-10 17:15:41 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
+2024-07-10 17:15:43 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated.
+2024-07-10 17:15:43 (WARNING): No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
+2024-07-10 17:15:43 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization']
+2024-07-10 17:15:45 (WARNING): log_summary for Tensorboard not supported
+

+

+
2024-07-10 17:17:33 (INFO): energy_mae: 4.4390, forcesx_mae: 0.0265, forcesy_mae: 0.0287, forcesz_mae: 0.0326, forces_mae: 0.0293, forces_cosine_similarity: -0.0255, forces_magnitude_error: 0.0412, energy_forces_within_threshold: 0.0000, loss: 4.5278, epoch: 0.5085
+2024-07-10 17:17:58 (INFO): energy_mae: 4.13e+00, forcesx_mae: 2.77e-02, forcesy_mae: 2.17e-02, forcesz_mae: 2.79e-02, forces_mae: 2.58e-02, forces_cosine_similarity: -1.25e-02, forces_magnitude_error: 3.38e-02, energy_forces_within_threshold: 0.00e+00, loss: 4.18e+00, lr: 5.00e-04, epoch: 6.78e-01, step: 4.00e+01
+2024-07-10 17:17:59 (INFO): Evaluating on val.
+2024-07-10 17:18:07 (INFO): energy_mae: 3.9977, forcesx_mae: 0.0090, forcesy_mae: 0.0131, forcesz_mae: 0.0090, forces_mae: 0.0104, forces_cosine_similarity: 0.0339, forces_magnitude_error: 0.0146, energy_forces_within_threshold: 0.0000, loss: 3.9749, epoch: 0.6780
+2024-07-10 17:18:08 (INFO): Predicting on test.
+2024-07-10 17:18:14 (INFO): Writing results to ./results/2024-07-10-17-14-40/ocp_predictions.npz
+2024-07-10 17:18:35 (INFO): energy_mae: 4.26e+00, forcesx_mae: 1.42e-02, forcesy_mae: 1.39e-02, forcesz_mae: 1.13e-02, forces_mae: 1.31e-02, forces_cosine_similarity: 4.83e-02, forces_magnitude_error: 1.46e-02, energy_forces_within_threshold: 0.00e+00, loss: 4.29e+00, lr: 5.00e-04, epoch: 8.47e-01, step: 5.00e+01
+2024-07-10 17:18:37 (INFO): Evaluating on val.
+2024-07-10 17:18:45 (INFO): energy_mae: 3.3149, forcesx_mae: 0.0231, forcesy_mae: 0.0234, forcesz_mae: 0.0183, forces_mae: 0.0216, forces_cosine_similarity: 0.0934, forces_magnitude_error: 0.0293, energy_forces_within_threshold: 0.0000, loss: 3.3103, epoch: 0.8475
+2024-07-10 17:19:04 (INFO): Total time taken: 198.395441532135
 

 

 

diff --git a/tutorials/intro.html b/tutorials/intro.html
index 1ee7d4d52..3a66da741 100644
--- a/tutorials/intro.html
+++ b/tutorials/intro.html
@@ -722,7 +722,7 @@ 
About the compute environment
 
/opt/hostedtoolcache/Python/3.11.9/x64/bin/python 3.11.9 (main, Jun 25 2024, 18:25:01) [GCC 11.4.0]
 fairchem is installed at /home/runner/work/fairchem/fairchem/src/fairchem
-fairchem repo is at git commit: bf2b26e
+fairchem repo is at git commit: 36a17ad
 numba: 0.60.0
 numpy: 1.26.4
 ase: 3.23.0
@@ -733,11 +733,11 @@ 
About the compute environment