Small fix painn #298
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Small fix painn #298
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update load_existing_model
add unscale_features_by_num_nodes_config
Add scaled by num_nodes option for feature prediction in variable graph size
* fix error name bugs * rm tracking error of node sum * reserved length for error lists
* Treat warnings as errors; Ignore deprecation warnings from tpl * fixup unscale assert
* Split device and device_name functions * Move data to device in loading rather than training (does NOT affect performance)
* frequency relaxed * frequency relaxed Co-authored-by: Massimiliano Lupo Pasini <7ml@ornl.gov>
* mapping of degree tensor to GPU * formatting fixed Co-authored-by: Massimiliano Lupo Pasini <7ml@ornl.gov>
data.batch is remapped to the same device as data.x
* added dashed red diagonal and use of empty dots in scatterplot * formatting fixed Co-authored-by: Massimiliano Lupo Pasini <7ml@ornl.gov>
* save train/val/test to pkls when total provided and reorganize data loading * remove raw in config
* fix an indexing bug in denormalization * add min/max loading from pkl
* wip: init profile * wip: add profile routine * wip: add profile routine * format fixed * Create profiler class * minor fix * Minor changes for merging * Move profile block to an upper level Co-authored-by: Massimiliano Lupo Pasini <7ml@ornl.gov> Co-authored-by: Massimiliano Lupo Pasini <massimiliano.lupo.pasini@gmail.com>
Co-authored-by: User <user@localadmins-Air.homenet.telecomitalia.it>
optimize get_head_indices with tensor operations
Remove num_nodes_list
Adding HYDRAGNN_MASTER_ADDR env to set custom DDP port.
Co-authored-by: Zhifan Ye <zhifanye@mail.ustc.edu.cn>
…NL#264) * init commit for enabling deepspeed * black formatting * optional deepspeed availability * if-else for model intialization * init commit * enable enable_deepspeed_ci ci * deepspeed required * mark pytest stages * try tests.xxx import * fixed: deepspeed_test * try test_examples only * try test_deepspeed only * clean up printing and ready to merge * disable deepspeed stage 3, maybe incompatible with CI machine * test network occupation * mark mpi for deepspeed * CI ready to deploy * fix dependency * minor format fix * double check merge * deepspeed out of optional * flush CI cache without deepspeed * remove auto CI for enable_deepspeed_ci branch * fix hash error & more elegant deepspeed-zero unit test --------- Co-authored-by: Zhifan Ye <zhifanye@mail.ustc.edu.cn>
…ing (ORNL#268) * init commit, tested work on frontier * update black formatting * amend template --------- Co-authored-by: Zhifan Ye <zye327@login07.frontier.olcf.ornl.gov>
* add energy linear regression * remove pdb * remove var_conf * fix for energy per atom * remove debug * fix energy per atom * fix for new energy calc * add npz output * save energy mean and linear regresison term * black * fix adios write * remove emean
* Update deephyper runs Update to capture all errors with try-except block. * Update gfm_deephyper_multi_perlmutter.py * Update distributed.py Use "SLURM_STEP_NODELIST" env, which is needed for HPO.
Adding PNAPlus Stack
* force tests, which required model arg, and some typo fixing in Lennard Jones * Add PNAPlus since it uses positions as well * formatting
* utils renamed and black formatting applied * bug fixed solved for tests * black formatting fixed * examples corrected * test_model_loadpred.py fixed * black formatting fixed * test_loss_and_activation_functions.py fixed * black formatting fixed * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of hydragnn into hhydragnn package * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of dataset forlder into datasets * reverting inadvertent automated refactoring of dataset forlder into datasets * git formatting fixed * Adagrad converted to Adamax * Additional changes to fix bugs and suggestions from erdem * imports fixed for LennardJones example * formatting fixed * imports in LJ_data.py fixed * import of graph utils fixed in LJ_data.py * import of setup.ddp() fixed in LennardJones * setup_log call fixed * get_summary_writer call fixed * additional calls fixed * black formatting fixedf
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Small fix here, it would have caused errors of hanging gradients when there's only one convolutional layer.