Readme and Examples for Tensor mode#632
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…em with global/local label, and support polar label normalization to speed up training. Examples and documentation not added yet
…_atomic, plus some implementation mentioned by Han Wang in May 7th's email
…e as ener mode, and will not cause conflict
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doc/Train a Deep Potential model to fit tensor like Dipole and Polarizability.md
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doc/Train a Deep Potential model to fit tensor like Dipole and Polarizability.md is not filename that compatible to the naming convention of doc files. Something like doc/train-tensor.md is preferred
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add Important hint for getting-started.md Update argcheck.py add Important hint for variables Update getting-started.md check validity of data systems. print help message add Important hint at getting-start.md (deepmodeling#622) * add Important hint for getting-started.md * add hint for some parameters * add Important hint for variables * Update argcheck.py * Update getting-started.md add doc of type embedding (deepmodeling#625) Optimized mkindex function in doc/conf.py and added two files in troubleshooting. (deepmodeling#619) support MPI and other atom_styles for LAMMPS atomic keyword (deepmodeling#628) * support MPI and other atom_styles for LAMMPS atomic keyword fix problems left in #44 * move out_each codes together * indent the code fix spell mistake (deepmodeling#638) Atention -> Attention Readme and Examples for Tensor mode (deepmodeling#632) * Complete modification of tensor training, support combination of system with global/local label, and support polar label normalization to speed up training. Examples and documentation not added yet * modify dipole json to pass ut test * change json file (second time) to pass ut test * modify test_data_modifier_shuffle.py file to fit new args rule * modify data_modifier_shuffle: from dipole.npy to atomic_dipole.npy * modify the name of pref_weight to pref and pref_atomic_weight to pref_atomic, plus some implementation mentioned by Han Wang in May 7th's email * fix a bug occuring in ut test * fix args of polar_se_a.json, to pass ut test * change args: from loss_type to type, so that the args will be the same as ener mode, and will not cause conflict * add examples and readme for tensor fitting mode in May 14 * change readmd content of tensor fit * change the file name of readme file of tensor fitting * Update train-fitting-tensor.md * Update train-fitting-tensor.md * Update train-fitting-tensor.md * change the explanation of why some of lcurve.out is 0 * Update train-fitting-tensor.md * Update train-fitting-tensor.md append to out_file when LAMMPS restarts (deepmodeling#640) This ensures the out file will not be override when LAMMPS restarts. This commit may be conflicted with deepmodeling#392. Commit @5597ea2b49f96e99a52a9779b04b6c12e5a79a04 should be dropped. add an example of C++ inference to doc (deepmodeling#652) * add an example of C++ inference to doc * fix broken link Add instructions for i-PI (deepmodeling#660) * Add instructions for i-PI * Update doc/getting-started.md Co-authored-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> Co-authored-by: tuoping <abby@DESKTOP-LV5KL0D.localdomain> Co-authored-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> Added doc for netsize setting, num_nodes specification, and sel setting in doc/troubleshooting/ (deepmodeling#657) fix issue 668 (deepmodeling#680) * fix bug of issue 668
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* Complete modification of tensor training, support combination of system with global/local label, and support polar label normalization to speed up training. Examples and documentation not added yet * modify dipole json to pass ut test * change json file (second time) to pass ut test * modify test_data_modifier_shuffle.py file to fit new args rule * modify data_modifier_shuffle: from dipole.npy to atomic_dipole.npy * modify the name of pref_weight to pref and pref_atomic_weight to pref_atomic, plus some implementation mentioned by Han Wang in May 7th's email * fix a bug occuring in ut test * fix args of polar_se_a.json, to pass ut test * change args: from loss_type to type, so that the args will be the same as ener mode, and will not cause conflict * add examples and readme for tensor fitting mode in May 14 * change readmd content of tensor fit * change the file name of readme file of tensor fitting * Update train-fitting-tensor.md * Update train-fitting-tensor.md * Update train-fitting-tensor.md * change the explanation of why some of lcurve.out is 0 * Update train-fitting-tensor.md * Update train-fitting-tensor.md
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Add a readme file for the tensor fitting, and add a dipole example and a polarizability example.
Author YWolfeee
Date May, 4, 2021