ML LOGFILE
Every VASP run with activated machine learning (INCAR contains ML_LMLFF = .TRUE.) will generate a file called ML_LOGFILE. In this log file a summary of settings and the development of quantities related to machine learning are presented in a compact, yet human-readable and post-processing friendly way. It complements the usual ab initio log output in the OUTCAR and OSZICAR files for machine learning VASP runs.
File layout
| Warning: Until machine learning is officially released in VASP the ML_LOGFILE file format may change without notice! |
Memory consumption estimation
* MEMORY INFORMATION *********************************************************************************************************************** Estimated memory consumption for ML force field generation (MB): Persistent allocations for force field : 516.9 | |-- CMAT for basis : 20.3 |-- FMAT for basis : 458.5 |-- DESC for basis : 2.6 |-- SOAP matrix : 2.3 Persistent allocations for ab initio data : 8.1 | |-- Ab initio data : 7.8 |-- Ab initio data (new) : 0.3 Temporary allocations for sparsification : 460.9 | |-- SVD matrices : 28.0 Other temporary allocations : 15.5 | |-- Descriptors : 4.7 |-- Regression : 6.5 |-- Prediction : 4.2 Total memory consumption : 1001.4 ********************************************************************************************************************************************
Machine learning setup
* MACHINE LEARNING SETTINGS **************************************************************************************************************** This section lists the available machine-learning related settings with a short description, their selected values and the INCAR tags. The column between the value and the INCAR tag may contain a "state indicator" highlighting the origin of the value. Here is a list of possible indicators: * : (empty) Tag was not provided in the INCAR file, a default value was chosen automatically. * (I) : Value was provided in the INCAR file. * (i) : Value was provided in the INCAR file, deprecated tag. * (!) : A value found in the INCAR file was overwritten by the contents of the ML_FF file. * (?) : The value for this tag was never set (please report this to the VASP developers). Tag values with associated units are given here in Angstrom/eV, if not specified otherwise. Please refer to the VASP online manual for a detailed description of available INCAR tags. General settings -------------------------------------------------------------------------------------------------------------------------------------------- Machine learning operation mode : 0 (I) ML_ISTART Descriptor settings -------------------------------------------------------------------------------------------------------------------------------------------- Radial descriptors: ------------------- Cutoff radius of radial descriptors : 5.00000E+00 ML_RCUT1 Gaussian width for broadening the atomic distribution for radial descriptors : 5.00000E-01 ML_SION1 Number of radial basis functions for atomic distribution for radial descriptors : 8 ML_MRB1 Angular descriptors: -------------------- Cutoff radius of angular descriptors : 5.00000E+00 ML_RCUT2 Gaussian width for broadening the atomic distribution for angular descriptors : 5.00000E-01 ML_SION2 Number of radial basis functions for atomic distribution for angular descriptors : 8 ML_MRB2 Maximum angular momentum quantum number of spherical harmonics used to expand atomic distributions : 4 ML_LMAX2 ...
Existing ab initio data
* AVAILABLE AB INITIO DATA ***************************************************************************************************************** Number of stored (maximum) ab initio structures: 114 ( 1500) * System 1 : 114 , name: "Si cubic diamond 2x2x2 super cell" * System 2 : 0 , name: "Si cubic diamond 2x2x2 super cell" Maximum number of atoms per element: * Element Si : 64 ********************************************************************************************************************************************
Main loop
Header
* MAIN LOOP ******************************************************************************************************************************** # STATUS ############################################################### # STATUS This line describes the overall status of each step. # STATUS # STATUS nstep ..... MD time step or input structure counter # STATUS state ..... One-word description of step action # STATUS - "accurate" (1) : Errors are low, force field is used # STATUS - "threshold" (2) : Errors exceeded threshold, structure is sampled from ab initio # STATUS - "learning" (3) : Stored configurations are used for training force field # STATUS - "critical" (4) : Errors are high, ab initio sampling and learning is enforced # STATUS - "predict" (5) : Force field is used in prediction mode only, no error checking # STATUS is ........ Integer representation of above one-word description (integer in parenthesis) # STATUS doabin .... Perform ab initio calculation (T/F) # STATUS iff ....... Force field available (T/F, False after startup hints to possible convergence problems) # STATUS nsample ... Number of steps since last reference structure collection (sample = T) # STATUS ngenff .... Number of steps since last force field generation (genff = T) # STATUS ############################################################### # STATUS nstep state is doabin iff nsample ngenff # STATUS 2 3 4 5 6 7 8 # STATUS ###############################################################
Body
-------------------------------------------------------------------------------- STATUS 82 learning 3 T T 0 72 LCONF 82 Si 1222 1228 SPRSC 82 129 129 Si 1228 1224 REGR 82 1 1 1.27238822E+00 5.73175466E-02 7.83203623E-12 REGR 82 1 2 1.28510216E+00 5.73084508E-02 7.75332075E-12 REGRF 82 1 3 1.29486873E+00 5.73015362E-02 7.69391276E-12 2.23430718E+16 5.75166077E+09 STDAB 82 1.28851006E-01 1.02791005E+00 1.07081172E+01 ERR 82 1.21269596E-02 2.35740491E-01 4.40365370E+00 CFE 82 2.71935242E-01 2.20681769E-01 7.30391193E-01 LASTE 82 1.63070075E-02 2.66475855E-01 7.17595981E+00 BEE 82 4.72039040E-05 1.03291046E-01 3.02999592E-02 9.56824349E-02 6.23077315E-01 4.66683801E-01 THRHIST 82 1 8.45535075E-02 THRHIST 82 2 8.99995395E-02 THRHIST 82 3 9.42765991E-02 THRHIST 82 4 9.37027237E-02 THRHIST 82 5 9.78682111E-02 THRHIST 82 6 1.02991465E-01 THRHIST 82 7 1.04972577E-01 THRHIST 82 8 1.02574658E-01 THRHIST 82 9 9.68150073E-02 THRHIST 82 10 8.90700596E-02 THRUPD 82 9.54674570E-02 9.56824349E-02 6.60216623E-02 1.06906899E-02 BEEF 82 4.58511233E-05 9.95065359E-02 2.94732909E-02 9.56824349E-02 6.03276708E-01 4.51396163E-01 --------------------------------------------------------------------------------
-------------------------------------------------------------------------------- STATUS 63 accurate 1 F T 3 53 BEEF 63 4.67236540E-05 1.09788403E-01 2.90204790E-02 9.56824349E-02 6.29349214E-01 4.74949548E-01 --------------------------------------------------------------------------------
Timing information
* TIMING INFORMATION *********************************************************************************************************************** Program part system clock (sec) cpu time (sec) ---------------------------------------------------|--------------------|------------------- Setup (file I/O, parameters,...) | 0.242 | 0.240 Descriptor and design matrix | 10.540 | 10.536 Sparsification of configurations | 9.183 | 9.177 Regression | 14.778 | 14.770 Prediction | 32.461 | 32.450 ---------------------------------------------------|--------------------|------------------- TOTAL | 67.204 | 67.173 ********************************************************************************************************************************************
Post-processing usage
# ERR ###################################################################### # ERR This line contains the RMSEs of the predictions with respect to ab initio results for the training data. # ERR # ERR nstep ......... MD time step or input structure counter # ERR rmse_energy ... RMSE of energies (eV atom^-1) # ERR rmse_force .... RMSE of forces (eV Angst^-1) # ERR rmse_stress ... RMSE of stress (kB) # ERR ###################################################################### # ERR nstep rmse_energy rmse_force rmse_stress # ERR 2 3 4 5 # ERR ###################################################################### ERR 2 8.77652825E-05 1.00592308E-02 2.68800480E-02 ERR 3 3.01865279E-05 1.06283576E-02 5.81209819E-02 ERR 4 1.52820686E-04 1.31384993E-02 1.10439716E-01 ERR 5 1.62739008E-04 1.74252575E-02 1.40488725E-01 ERR 6 2.97462508E-04 2.32615279E-02 1.79092561E-01 ERR 7 2.10891509E-04 2.79123925E-02 1.94566420E-01 ERR 8 3.26150852E-04 3.15081244E-02 1.76637577E-01 ERR 9 7.03479132E-04 3.42249550E-02 1.66830771E-01 ERR 10 2.41808229E-04 3.54422133E-02 1.80246157E-01 ERR 11 2.46299647E-04 3.70102675E-02 2.01262013E-01 ERR 12 3.57654922E-04 3.93143970E-02 2.20533745E-01 ERR 14 1.95974374E-04 4.31813231E-02 2.44026531E-01 ERR 15 4.94080997E-04 4.73774930E-02 2.74308998E-01 ERR 16 9.62150633E-04 5.07005683E-02 3.17482301E-01 ERR 18 1.31336233E-03 5.39222716E-02 3.25526268E-01 ERR 21 1.07020831E-03 5.67663475E-02 3.04995023E-01 ERR 24 9.88977484E-04 6.37987961E-02 3.83686143E-01 ERR 26 9.63361971E-04 6.81972633E-02 4.92021943E-01 ERR 29 1.81730719E-03 7.47758864E-02 6.38563225E-01