After reinstalling deepkit today, after training the model to generate graph.pb, the following error appeared in lammps, what is the reason? I tried graph.pb that was trained before updating it and it works fine
Info of model(s):
using 1 model(s): graph.pb
rcut in model: 6.5
ntypes in model: 1
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 16.5
ghost atom cutoff = 16.5
binsize = 8.25, bins = 2 2 2
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair deepmd, perpetual
attributes: full, newton on
pair build: full/bin/atomonly
stencil: full/bin/3d
bin: standard
Setting up Verlet run ...
Unit style : metal
Current step : 0
Time step : 0.001
INVALID_ARGUMENT: Incompatible shapes: [1,96] vs. [1,4020]
[[{{node gradients/mul_4_grad/BroadcastGradientArgs}}]]
ERROR: DeePMD-kit Error: TensorFlow Error: INVALID_ARGUMENT: Incompatible shapes: [1,96] vs. [1,4020]
[[{node gradients/mul_4_grad/BroadcastGradientArgs}]] (/home/conda/feedstock_root/build_artifacts/libdeepmd_1678813995417/work/source/lmp/pair_deepmd.cpp:471)
Last command: run
DeePMD-kit Version
2.2
TensorFlow Version
.
Python Version, CUDA Version, GCC Version, LAMMPS Version, etc
No response
Details
After reinstalling deepkit today, after training the model to generate graph.pb, the following error appeared in lammps, what is the reason? I tried graph.pb that was trained before updating it and it works fine
njzjz
commented
1 year ago
Summary
After reinstalling deepkit today, after training the model to generate graph.pb, the following error appeared in lammps, what is the reason? I tried graph.pb that was trained before updating it and it works fine
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Your simulation uses code contributions which should be cited:
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Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule Neighbor list info ... update every 1 steps, delay 0 steps, check yes max neighbors/atom: 2000, page size: 100000 master list distance cutoff = 16.5 ghost atom cutoff = 16.5 binsize = 8.25, bins = 2 2 2 1 neighbor lists, perpetual/occasional/extra = 1 0 0 (1) pair deepmd, perpetual attributes: full, newton on pair build: full/bin/atomonly stencil: full/bin/3d bin: standard Setting up Verlet run ... Unit style : metal Current step : 0 Time step : 0.001 INVALID_ARGUMENT: Incompatible shapes: [1,96] vs. [1,4020] [[{{node gradients/mul_4_grad/BroadcastGradientArgs}}]] ERROR: DeePMD-kit Error: TensorFlow Error: INVALID_ARGUMENT: Incompatible shapes: [1,96] vs. [1,4020] [[{node gradients/mul_4_grad/BroadcastGradientArgs}]] (/home/conda/feedstock_root/build_artifacts/libdeepmd_1678813995417/work/source/lmp/pair_deepmd.cpp:471) Last command: run
DeePMD-kit Version
2.2
TensorFlow Version
.
Python Version, CUDA Version, GCC Version, LAMMPS Version, etc
No response
Details
After reinstalling deepkit today, after training the model to generate graph.pb, the following error appeared in lammps, what is the reason? I tried graph.pb that was trained before updating it and it works fine