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In training a system about Liquid_Methanol in a linux system, I found an error saying "floating point exception (in Japanese: 浮動小数点例外). I know that this message occurs in a case that I divide some number by zero. However, I do not know where this calculation is carried out and how to fix this problem. Please let me know how should I do?
my tensor flow and deepmd's version is here
deepmd-kit 1.1.5
libdeepmd 1.2.0
libtensorflow_cc 2.1.0
tensorflow 1.14.0
tensorflow-base 2.2.0
tensorflow-estimator 2.2.0
in other training offered in samples, I can train it successfully. Then I think something goes wrong with my input file...
This discussion was converted from issue #250 on December 24, 2020 15:39.
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Hello,
In training a system about Liquid_Methanol in a linux system, I found an error saying "floating point exception (in Japanese: 浮動小数点例外). I know that this message occurs in a case that I divide some number by zero. However, I do not know where this calculation is carried out and how to fix this problem. Please let me know how should I do?
this is a input json file I used
{
"_comment": " model parameters",
"model_type": "se_r",
"model": {
"type_map": ["C", "O", "H", "H"],
"descriptor": {
"type": "se_r",
"sel": [46, 46, 138, 46],
"rcut_smth": 1.00,
"rcut": 6.00,
"neuron": [5, 10, 20],
"resnet_dt": false,
"seed": 1,
"_comment": " that's all"
},
"fitting_net" :{
"neuron": [120, 120, 120],
"resnet_dt": true,
"seed": 1,
"_comment": "that's all"
},
"_comment": " that's all"
},
"learning_rate" : {
"start_lr": 0.005,
"decay_steps": 5000,
"decay_rate": 0.95,
"_comment": " that's all"
},
"loss" : {
"start_pref_e": 0.02,
"limit_pref_e": 1,
"start_pref_f": 1000,
"limit_pref_f": 1,
"start_pref_v": 0,
"limit_pref_v": 0,
"_comment": " that's all"
},
"_comment": " traing controls",
"training" : {
"systems": ["data/"],
"set_prefix": "set",
"_comment:stop_batch": 570000,
"stop_batch": 1000000,
"batch_size": 1,
"seed": 1,
"_comment": " display and restart",
"_comment": " frequencies counted in batch",
"disp_file": "lcurve.out",
"disp_freq": 100,
"numb_test": 10,
"save_freq": 1000,
"save_ckpt": "model.ckpt",
"load_ckpt": "model.ckpt",
"disp_training":true,
"time_training":true,
"profiling": false,
"profiling_file": "timeline.json",
"_comment": "that's all"
},
"_comment": "that's all"
}
my tensor flow and deepmd's version is here
deepmd-kit 1.1.5
libdeepmd 1.2.0
libtensorflow_cc 2.1.0
tensorflow 1.14.0
tensorflow-base 2.2.0
tensorflow-estimator 2.2.0
in other training offered in samples, I can train it successfully. Then I think something goes wrong with my input file...
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