Calculate virials and stress with vectors to get atomic virial

[pobo95]

Description

Calculate virials and stress with vectors instead of displacement .

Motivation and Formula

Motivation
To get atomic virial for NPT simulations and stress/atom in LAMMPS .

Formula

How Has It Been Tested?

virials and stress ouput of vectors and displacement are consistent.

based on MACE ver.0.3.4
You can use with this code to pair LAMMPS

Reference
Yu, H., Zhong, Y., Ji, J., Gong, X. & Xiang, H. Preprint at https://doi.org/10.26434/chemrxiv-2022-h6f69 (2022).

[wcwitt]

Hi @pobo95, would you please email me at [email protected]? I think we should discuss this PR on a Zoom call.

[pobo95]

@wcwitt Yes of course! I just sent you an email.

[ilyes319]

@wcwitt Looked at the PR and it seems great, what do you think?

[yyhb777]

Firstly, I would like to express my sincere gratitude for your efforts in improving the code. I have attempted to use the code from the atom_virial branch for training, and subsequently employed pair_mace to integrate it with LAMMPS. However, upon running the Green-Kubo simulation in LAMMPS, I encountered the following error:
”Exception:Expected Tensor but got None
Exception raised from reportToTensorTypeError at ../aten/src/ATen/core/ivalue.cpp:950 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x2ab2a9e87d77 in /share/home/mace_GK/libtorch/lib/libc10.so)
frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x2ab2a9e51abb in /share/home/mace_GK/libtorch/lib/libc10.so)
frame #2: c10::IValue::reportToTensorTypeError() const + 0x58 (0x2ab2add61b98 in /share/home/mace_GK/libtorch/lib/libtorch_cpu.so)
frame #3: /share/home/mace_GK/lammps-mace/build/lmp() [0x8ff28d]
frame #4: /share/home/mace_GK/lammps-mace/build/lmp() [0x607060]
frame #5: /share/home/mace_GK/lammps-mace/build/lmp() [0x593498]
frame #6: /share/home/mace_GK/lammps-mace/build/lmp() [0x4971db]
frame #7: /share/home/mace_GK/lammps-mace/build/lmp() [0x4974bd]
frame #8: /share/home/mace_GK/lammps-mace/build/lmp() [0x488138]
frame #9: __libc_start_main + 0xf5 (0x2ab2c5710c05 in /lib64/libc.so.6)
frame #10: /share/home/mace_GK/lammps-mace/build/lmp() [0x489c67]
application called MPI_Abort(MPI_COMM_WORLD, 1) - process 0“

I am writing to inquire whether this issue might be related to the model I trained still not being able to output the atom virial. Enclosed are my training input files and LAMMPS input files. I look forward to your response.
input.zip

[pobo95]

@yyhb777
Can you show me the log with error_table=PerAtomRMSEstressvirials?
stress/virial information is handled as None if missing, but it seems like there is no stress/virial information during the training process.
Also, could you share your computing environment and training set?

[pobo95]

@yyhb777
Wolud you like to try it with these files?
Si_test.zip

mace_run_train     --name="mace"     --train_file="train.xyz"     --valid_fraction=0.05     --test_file="validate.xyz"     --E0s={14:-0.08755009}     --model="MACE"     --num_interactions=2     --hidden_irreps='64x0e + 64x1o'     --max_L=1     --correlation=2     --r_max=5.0     --forces_weight=1000     --energy_weight=10     --batch_size=5     --valid_batch_size=2     --max_num_epochs=50   --compute_stress=”true”  --start_swa=10     --scheduler_patience=5     --patience=15     --eval_interval=3     --ema     --swa     --swa_forces_weight=10     --default_dtype="float64"    --device=cuda     --seed=123     --restart_latest     --save_cpu --error_table=PerAtomRMSEstressvirials 

[yyhb777]

@pobo95
I would like to begin by sincerely thanking you for your prompt response. For the sake of clarity, I have used my computational environment to train the Si_test.zip file you provided and have subsequently converted the model for LAMMPS-GK simulations through the create_lammps_model.py script. I have provided the following three files, two of which could not be uploaded due to file size restrictions and will sent to your email. Please check your inbox at your convenience:
1.env_mace_gk.zip: my computational environment.
2.Si_train and MD simulation.zip: The training and MD simulation files for Si_test.zip, which include a detailed README for clarification.
3.software-packages.zip: The software packages employed in the training and MD simulations, with the LAMMPS executable(lmp) located at /lammps-mace/build and the build.sh script used for the compilation process.
Once again, thank you for your valuable time and assistance.
Si_train and MD simulation.zip

[edwardsmith999]

Hi , thank you @wcwitt, @yyhb777 for the excellent mace code and @pobo95 for the additional to include stresses per atom. Given getting something working with LAMMPS is a little tricky (especially with C++ code, the variation in LAMMPS version, limited python support, etc, etc), it would be useful as a first step to simply get the get_stresses working in the ASE code. I have merged pobo95 code into the latest main branch in a forked version here https://github.com/edwardsmith999/mace (with a little uncertainty about if batch/displacement arguments are replaced needed). I have then added the required code so ASE has the get_stresses function working. This satisfies the conditions:

atoms.cell.volume*atoms.get_stress() == np.sum(atoms.get_stresses(),0)

I don't want to overwrite pobo95's contribution or confuse things with another pull request but it would be useful to have this functionality in if possible. Please let me know if I can help further getting this included.

[pobo95]

Hi! @edwardsmith999
Thanks for your work on this! I really appreciate you taking the time to merge and improve the functionality. If everything is working correctly and aligns with what you need, feel free to proced.
I don't mind how this gets integrated, just let me know if you need any input from my side.