Why not correctly predict the energy by using deepmd.calculator in ASE? #1366
Description
Dear developers,
I want to predict the energy using deepmd.calculator in ASE module according to the https://github.com/deepmodeling/deepmd-kit/blob/master/doc/third-party/ase.md, but some errors occur. The obtained energy is not correct.
My code is :
`#!/bin/env python
from ase import Atoms
from deepmd.calculator import DP
import ase.io as IO
system_ase = IO.read("OUTCAR")
print(system_ase.get_potential_energy())
import dpdata
system_dpdata = dpdata.LabeledSystem("OUTCAR", fmt="vasp/outcar")
print(system_dpdata["energies"][0])
atype = system_dpdata["atom_types"]
system_ase_tmp = Atoms("Li12Co12O24", positions=system_ase.get_positions(), cell=system_ase.get_cell(), calculator=DP(model="graph.000.pb"))
print(system_ase_tmp.get_potential_energy())
from deepmd.infer import DeepPot
import numpy as np
dp = DeepPot("graph.000.pb")
coordinate = np.array(system_ase.get_positions()).reshape([1, -1])
cell = np.array(system_ase.get_cell()).reshape([1, -1])
e, f, v = dp.eval(coordinate, cell, atype)
print(e)`
the output of the code is:
WARNING:tensorflow:From /data/hutaiping/hutaiping/bin/Software/anaconda3/envs/deepmodeling/lib/python3.9/site-packages/tensorflow/python/compat/v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
WARNING:root:Environment variable KMP_BLOCKTIME is empty. Use the default value 0
WARNING:root:Environment variable KMP_AFFINITY is empty. Use the default value granularity=fine,verbose,compact,1,0
/data/hutaiping/hutaiping/bin/Software/anaconda3/envs/deepmodeling/lib/python3.9/importlib/init.py:169: UserWarning: The NumPy module was reloaded (imported a second time). This can in some cases result in small but subtle issues and is discouraged.
_bootstrap._exec(spec, module)
OMP: Info #155: KMP_AFFINITY: Initial OS proc set respected: 0-7
OMP: Info #216: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #216: KMP_AFFINITY: cpuid leaf 11 not supported.
OMP: Info #216: KMP_AFFINITY: decoding legacy APIC ids.
OMP: Info #157: KMP_AFFINITY: 8 available OS procs
OMP: Info #158: KMP_AFFINITY: Uniform topology
OMP: Info #287: KMP_AFFINITY: topology layer "LL cache" is equivalent to "socket".
OMP: Info #192: KMP_AFFINITY: 1 socket x 4 cores/socket x 2 threads/core (4 total cores)
OMP: Info #218: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #172: KMP_AFFINITY: OS proc 0 maps to socket 0 core 0 thread 0
OMP: Info #172: KMP_AFFINITY: OS proc 1 maps to socket 0 core 0 thread 1
OMP: Info #172: KMP_AFFINITY: OS proc 2 maps to socket 0 core 1 thread 0
OMP: Info #172: KMP_AFFINITY: OS proc 3 maps to socket 0 core 1 thread 1
OMP: Info #172: KMP_AFFINITY: OS proc 4 maps to socket 0 core 2 thread 0
OMP: Info #172: KMP_AFFINITY: OS proc 5 maps to socket 0 core 2 thread 1
OMP: Info #172: KMP_AFFINITY: OS proc 6 maps to socket 0 core 3 thread 0
OMP: Info #172: KMP_AFFINITY: OS proc 7 maps to socket 0 core 3 thread 1
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 823851 thread 0 bound to OS proc set 0
-274.46677386
-274.46677386
2021-12-21 09:57:57.948274: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-12-21 09:57:57.948639: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
2021-12-21 09:57:57.969967: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2499995000 Hz
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 825240 thread 1 bound to OS proc set 2
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 825998 thread 3 bound to OS proc set 6
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 825999 thread 4 bound to OS proc set 1
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826000 thread 5 bound to OS proc set 3
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826002 thread 7 bound to OS proc set 7
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826003 thread 8 bound to OS proc set 0
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826001 thread 6 bound to OS proc set 5
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 825997 thread 2 bound to OS proc set 4
-157.2026545916724
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 825241 thread 9 bound to OS proc set 2
OMP: Info #254:
test.tar.gz
KMP_AFFINITY: pid 823851 tid 826769 thread 11 bound to OS proc set 6
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826771 thread 13 bound to OS proc set 3
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826772 thread 14 bound to OS proc set 5
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826774 thread 16 bound to OS proc set 0
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826768 thread 10 bound to OS proc set 4
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826770 thread 12 bound to OS proc set 1
OMP: Info #254: KMP_AFFINITY: pid 823851 tid 826773 thread 15 bound to OS proc set 7
[[-274.50289425]]
my python version is 3.9.7, deepmd kit version is 2.0.3.
Here I attach all my files.
test.tar.gz