From 67b9f44762cafb0cb634ac6fe3f1e7674f567016 Mon Sep 17 00:00:00 2001 From: Dongsun Yoo Date: Tue, 28 Jan 2020 17:46:40 +0900 Subject: [PATCH 1/2] Fix broken link in documents --- docs/examples/examples.rst | 4 ++-- docs/features/symmetry_function/symmetry_function.rst | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/examples/examples.rst b/docs/examples/examples.rst index b3b59fa..c4a15d9 100644 --- a/docs/examples/examples.rst +++ b/docs/examples/examples.rst @@ -22,9 +22,9 @@ Generate NNP To generate NNP using symmetry function and neural network, you need three types of input file (input.yaml, str_list, params_XX) -as described in :doc:`/tutorials/tutorial:md-simulation-with-lammps` section. +as described in :doc:`/tutorials/tutorial` section. The example files except params_Si and params_O are introduced below. -Detail of params_Si and params_O can be found in :doc:`/features/symmetry_function/symmetry_function:inputs` section. +Detail of params_Si and params_O can be found in :doc:`/features/symmetry_function/symmetry_function` section. Input files introduced in this section can be found in :code:`SIMPLE-NN/examples/SiO2/generate_NNP`. diff --git a/docs/features/symmetry_function/symmetry_function.rst b/docs/features/symmetry_function/symmetry_function.rst index 689d68e..a526daf 100644 --- a/docs/features/symmetry_function/symmetry_function.rst +++ b/docs/features/symmetry_function/symmetry_function.rst @@ -101,7 +101,7 @@ Each parameter indicates (SF means symmetry function) :: The number inside the indicates the number of parameters. -First column indicates the type of symmetry function. Currently, G2 (2), G4 (4), and G5 (5) are available (defined in the reference[#f1]_). +First column indicates the type of symmetry function. Currently, G2 (2), G4 (4), and G5 (5) are available. Second and third column indicates the type index of neighbor atoms which starts from 1. (The order of type index need to be the same as the order of the :code:`atom_types` tag indicated in :code:`input.yaml`) From a48b2c714a2e2d41277facdc50532d4cec97a903 Mon Sep 17 00:00:00 2001 From: JisuJung928 Date: Wed, 29 Jan 2020 11:04:16 +0900 Subject: [PATCH 2/2] manual minor fix --- README.md | 2 +- docs/models/hdnn/hdnn.rst | 5 +++-- simple_nn/models/neural_network.py | 3 +-- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index e5b87fb..ad93ffd 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ If you use SIMPLE-NN, please cite this article: K. Lee, D. Yoo, W. Jeong, S. Han, SIMPLE-NN: An efficient package for training and executing neural-network interatomic potentials, *Computer Physics Communications* (2019), https://doi.org/10.1016/j.cpc.2019.04.014. Here do we describe minimal instruction to run the example of SIMPLE-NN -If you want more information such as tuning parameters, please visit our online manual(https://mtcg.snu.ac.kr/doc/index.html) +If you want more information such as tuning parameters, please visit our online manual(https://simple-nn.readthedocs.io) ## Installation SIMPLE-NN use Tensorflow and mpi4py(optional). diff --git a/docs/models/hdnn/hdnn.rst b/docs/models/hdnn/hdnn.rst index 9631d79..7f424c4 100644 --- a/docs/models/hdnn/hdnn.rst +++ b/docs/models/hdnn/hdnn.rst @@ -53,13 +53,14 @@ Network related parameter If :code:`true`, both energy and force are used for training. * :code:`force_coeff`\: (float, default: 0.1) - Ratio of force_loss to energy_loss in total_loss + Ratio of force loss to energy loss in total loss * :code:`use_stress`\: (boolean, default: false) If :code:`true`, both energy and stress are used for training. + (Caution : The unit of stress RMSE written in LOG file is kbar.) * :code:`stress_coeff`\: (float, default: 0.00001) - Ratio of stress_loss to energy_loss in total_loss + Ratio of stress loss to energy loss in total loss * :code:`stddev`\: (float, default: 0.3) Standard deviation for weights initialization. diff --git a/simple_nn/models/neural_network.py b/simple_nn/models/neural_network.py index e48cdaa..e9ab08a 100644 --- a/simple_nn/models/neural_network.py +++ b/simple_nn/models/neural_network.py @@ -42,7 +42,7 @@ def __init__(self): 'params': dict(), }, 'use_force': True, - 'use_stress': True, + 'use_stress': False, 'double_precision': True, 'weight_initializer': { 'type': 'truncated normal', @@ -176,7 +176,6 @@ def _make_model(self): if self.inputs['continue'] == 'weights': saved_weights = read_lammps_potential('potential_saved') - #acti_func = 'selu' #acti_func = 'elu' #acti_func = 'sigmoid' #acti_func = 'tanh'