Merge pull request #116 from deepmodeling/devel

merge devel into master

Author: amcadmus

.travis.yml

@@ -31,6 +31,16 @@ matrix:
       - CC=gcc-4.8
       - CXX=g++-4.8
       - TENSORFLOW_VERSION=1.14
+    - python: 3.6
+      env: 
+      - CC=gcc-5
+      - CXX=g++-5
+      - TENSORFLOW_VERSION=1.14
+    - python: 3.6
+      env: 
+      - CC=gcc-8
+      - CXX=g++-8
+      - TENSORFLOW_VERSION=1.14
     - python: 3.7
       env: 
       - CC=gcc-5

README.md

@@ -9,8 +9,11 @@
  	- [License and credits](#license-and-credits)
  	- [Deep Potential in a nutshell](#deep-potential-in-a-nutshell)
 - [Download and install](#download-and-install)
+    - [Easy installation methods](#easy-installation-methods)
+      - [With Docker](#with-docker)
+      - [With conda](#with-conda)
+      - [Offline packages](#offline-packages)
     - [Install the python interaction](#install-the-python-interface)
-      - [Easy installation methods](#easy-installation-methods)
       - [Install the Tensorflow's python interface](#install-the-tensorflows-python-interface)
       - [Install the DeePMD-kit's python interface](#install-the-deepmd-kits-python-interface)
     - [Install the C++ interface](#install-the-c-interface)
@@ -83,11 +86,29 @@ In addition to building up potential energy models, DeePMD-kit can also be used
 
 Please follow our [github](https://github.com/deepmodeling/deepmd-kit) webpage to see the latest released version and development version.
 
-## Install the python interface 
+## Easy installation methods
+There various easy methods to install DeePMD-kit. Choose one that you prefer. If you want to build by yourself, jump to the next two sections.
+
+### With Docker
+A docker for installing the DeePMD-kit on CentOS 7 is available [here](https://github.com/frankhan91/deepmd-kit_docker).
+
+### With conda
+DeePMD-kit is avaiable with [conda](https://github.com/conda/conda). Install [Anaconda](https://www.anaconda.com/distribution/#download-section) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) first.
+
+To install the CPU version:
+```bash
+conda install deepmd-kit=*=*cpu lammps-dp=*=*cpu -c deepmodeling
+```
+
+To install the GPU version containing [CUDA 10.0](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver):
+```bash
+conda install deepmd-kit=*=*gpu lammps-dp=*=*gpu -c deepmodeling
+```
 
-### Easy installation methods
-A docker for installing the DeePMD-kit on CentOS 7 is available [here](https://github.com/frankhan91/deepmd-kit_docker). We are currently working on installation methods using the `conda` package management system and `pip` tools. Hope these will come out soon.
+### Offline packages
+Both CPU and GPU version offline package are avaiable in [the Releases page](https://github.com/deepmodeling/deepmd-kit/releases).
 
+## Install the python interface 
 ### Install the Tensorflow's python interface
 First, check the python version and compiler version on your machine 
 ```bash
@@ -102,6 +123,14 @@ source $tensorflow_venv/bin/activate
 pip install --upgrade pip
 pip install --upgrade tensorflow==1.14.0
 ```
+It is notice that everytime a new shell is started and one wants to use `DeePMD-kit`, the virtual environment should be activated by 
+```bash
+source $tensorflow_venv/bin/activate
+```
+if one wants to skip out of the virtual environment, he/she can do
+```bash
+deactivate
+```
 If one has multiple python interpreters named like python3.x, it can be specified by, for example
 ```bash
 virtualenv -p python3.7 $tensorflow_venv
@@ -483,7 +512,7 @@ Running an MD simulation with LAMMPS is simpler. In the LAMMPS input file, one n
 pair_style     deepmd graph.pb
 pair_coeff     
 ```
-where `graph.pb` is the file name of the frozen model. The `pair_coeff` should be left blank. It should be noted that LAMMPS counts atom types starting from 1, therefore, all LAMMPS atom type will be firstly subtracted by 1, and then passed into the DeePMD-kit engine to compute the interactions. A detailed documentation of this pair style is [here](doc/lammps-pair-style-deepmd.md).
+where `graph.pb` is the file name of the frozen model. The `pair_coeff` should be left blank. It should be noted that LAMMPS counts atom types starting from 1, therefore, all LAMMPS atom type will be firstly subtracted by 1, and then passed into the DeePMD-kit engine to compute the interactions. [A detailed documentation of this pair style is available.](doc/lammps-pair-style-deepmd.md).
 
 ### Long-range interaction
 The reciprocal space part of the long-range interaction can be calculated by LAMMPS command `kspace_style`. To use it with DeePMD-kit, one writes 
@@ -533,11 +562,7 @@ If other unexpected problems occur, you're welcome to contact us for help.
 
 When the version of DeePMD-kit used to training model is different from the that of DeePMD-kit running MDs, one has the problem of model compatability.
 
-DeePMD-kit guarantees that the codes with the same major and minor revisions are compatible. That is to say v0.12.5 is compatible to v0.12.0, but is not compatible to v0.11.0. When way of fixing it is to restart the training with the new revisions and a slightly increased `stop_batch`, say 1,000,000 to 1,001,000 if the `save_freq` was set to 1,000. Typically one runs
-```bash
-dp train --restart model.ckpt revised_input.json
-```
-and freeze the new model.
+DeePMD-kit guarantees that the codes with the same major and minor revisions are compatible. That is to say v0.12.5 is compatible to v0.12.0, but is not compatible to v0.11.0 nor v1.0.0. 
 
 ## Installation: inadequate versions of gcc/g++
 Sometimes you may use a gcc/g++ of version <4.9. If you have a gcc/g++ of version > 4.9, say, 7.2.0, you may choose to use it by doing 

deepmd/__init__.py

@@ -1,8 +1,9 @@
 from .env import set_mkl
-from .DeepEval  import DeepEval
-from .DeepPot   import DeepPot
-from .DeepPolar import DeepPolar
-from .DeepWFC   import DeepWFC
+from .DeepEval   import DeepEval
+from .DeepPot    import DeepPot
+from .DeepDipole import DeepDipole
+from .DeepPolar  import DeepPolar
+from .DeepWFC    import DeepWFC
 
 set_mkl()
 

doc/lammps-pair-style-deepmd.md

@@ -35,13 +35,13 @@ This pair style takes the deep potential defined in a model file that usually ha
 
 The model deviation evalulate the consistency of the force predictions from multiple models. By default, only the maximal, minimal and averge model deviations are output. If the key `atomic` is set, then the model deviation of force prediction of each atom will be output.
 
-By default, the model deviation is output in absolute value. If the keyword `relative` is set, then the relative model deviation will be output, which is defined by
+By default, the model deviation is output in absolute value. If the keyword `relative` is set, then the relative model deviation will be output. The relative model deviation of the force on atom `i` is defined by
 ```math
-         |Df|
-Ef = -------------
-      |f| + level
+           |Df_i|
+Ef_i = -------------
+       |f_i| + level
 ```
-where `Df` is the model deviation of a force, `|f|` is the norm of the force and `level` is provided as the parameter of the keyword `relative`.
+where `Df_i` is the absolute model deviation of the force on atom `i`, `|f_i|` is the norm of the the force and `level` is provided as the parameter of the keyword `relative`.
 
 
 ## Restrictions
@@ -50,6 +50,8 @@ where `Df` is the model deviation of a force, `|f|` is the norm of the force and
 
 - The `atom_style` of the system should be `atomic`.
 
+- When using the `atomic` key word of `deepmd` is set, one should not use this pair style with MPI parallelization.
+
 
 [DP]:https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.120.143001
 [DP-SE]:https://arxiv.org/abs/1805.09003

examples/fparam/data/.gitignore

@@ -1,2 +1,2 @@
-*raw
-
+*.raw
+convert_aparam.py