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Add united test for trainer.test and description in the example #165

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merged 15 commits into from
Sep 13, 2023
Merged

Add united test for trainer.test and description in the example #165

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ccad860
Optimize the Atoms2Graph and fixed the np.meshgrid
kenko911 Aug 29, 2023
bafbc16
put unittests
kenko911 Aug 29, 2023
120a36e
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 29, 2023
9e1a24b
improve the _three_body.py and test_M3GNetCalculator in test_ase.py
kenko911 Aug 29, 2023
1057435
Merge branch 'main' into main
shyuep Aug 29, 2023
a65b926
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 31, 2023
83b8eb8
add cpu() in ase.py and compute.py to enable the GPU usage for MatGL-…
kenko911 Aug 31, 2023
184c0ec
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 31, 2023
7db50e7
included the unit-test for hessian test_ase.py to improve the coverag…
kenko911 Sep 1, 2023
5b3ea43
Merge branch 'main' of https://github.com/kenko911/matgl
kenko911 Sep 1, 2023
517ba07
Merge branch 'materialsvirtuallab:main' into main
kenko911 Sep 3, 2023
8d2e6ef
Merge branch 'materialsvirtuallab:main' into main
kenko911 Sep 5, 2023
1253ba5
remove reducdant torch.unique for finding the maximum three_body inde…
kenko911 Sep 5, 2023
555a001
Merge branch 'materialsvirtuallab:main' into main
kenko911 Sep 13, 2023
ca79fab
add united test for trainer.test and description in the example
kenko911 Sep 13, 2023
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7 changes: 4 additions & 3 deletions examples/Training a M3GNet Potential with PyTorch Lightning.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -268,7 +268,8 @@
"source": [
"# If you wish to disable GPU or MPS (M1 mac) training, use the accelerator=\"cpu\" kwarg.\n",
"logger = CSVLogger(\"logs\", name=\"M3GNet_training\")\n",
"trainer = pl.Trainer(max_epochs=1, accelerator=\"cpu\", logger=logger)\n",
"# Inference mode = False is required for calculating forces, stress in test mode and prediction mode\n",
"trainer = pl.Trainer(max_epochs=1, accelerator=\"cpu\", logger=logger, inference_mode=False)\n",
"trainer.fit(model=lit_module, train_dataloaders=train_loader, val_dataloaders=val_loader)"
]
},
Expand Down Expand Up @@ -405,7 +406,7 @@
"source": [
"# If you wish to disable GPU or MPS (M1 mac) training, use the accelerator=\"cpu\" kwarg.\n",
"logger = CSVLogger(\"logs\", name=\"M3GNet_finetuning\")\n",
"trainer = pl.Trainer(max_epochs=1, accelerator=\"cpu\", logger=logger)\n",
"trainer = pl.Trainer(max_epochs=1, accelerator=\"cpu\", logger=logger, inference_mode=False)\n",
"trainer.fit(model=lit_module_finetune, train_dataloaders=train_loader, val_dataloaders=val_loader)"
]
},
Expand Down Expand Up @@ -467,7 +468,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
"version": "3.10.9"
}
},
"nbformat": 4,
Expand Down
3 changes: 2 additions & 1 deletion tests/utils/test_training.py
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Expand Up @@ -113,9 +113,10 @@ def test_m3gnet_training(self, LiFePO4, BaNiO3):
model = M3GNet(element_types=element_types, is_intensive=False)
lit_model = PotentialLightningModule(model=model, stress_weight=0.0001)
# We will use CPU if MPS is available since there is a serious bug.
trainer = pl.Trainer(max_epochs=5, accelerator=device)
trainer = pl.Trainer(max_epochs=5, accelerator=device, inference_mode=False)

trainer.fit(model=lit_model, train_dataloaders=train_loader, val_dataloaders=val_loader)
trainer.test(lit_model, dataloaders=test_loader)

pred_LFP_energy = model.predict_structure(LiFePO4)
pred_BNO_energy = model.predict_structure(BaNiO3)
Expand Down