Merge pull request #2508 from athomps/mliappy3
Add support for Python based models to the MLIAP package
This commit is contained in:
Axel Kohlmeyer
@ -373,7 +373,7 @@ else()
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set(CUDA_REQUEST_PIC)
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endif()
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foreach(PKG_WITH_INCL KSPACE PYTHON VORONOI USER-COLVARS USER-MOLFILE USER-NETCDF USER-PLUMED USER-QMMM
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foreach(PKG_WITH_INCL KSPACE PYTHON MLIAP VORONOI USER-COLVARS USER-MOLFILE USER-NETCDF USER-PLUMED USER-QMMM
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USER-QUIP USER-SCAFACOS USER-SMD USER-VTK KIM LATTE MESSAGE MSCG COMPRESS)
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if(PKG_${PKG_WITH_INCL})
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include(Packages/${PKG_WITH_INCL})
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30
cmake/Modules/FindCythonize.cmake
Normal file
30
cmake/Modules/FindCythonize.cmake
Normal file
@ -0,0 +1,30 @@
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# Find the Cythonize tool.
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#
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# This code sets the following variables:
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#
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# Cythonize_EXECUTABLE
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#
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# adapted from https://github.com/cmarshall108/cython-cmake-example/blob/master/cmake/FindCython.cmake
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#=============================================================================
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if(CMAKE_VERSION VERSION_LESS 3.12)
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find_package(PythonInterp 3.6 QUIET) # Deprecated since version 3.12
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if(PYTHONINTERP_FOUND)
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set(Python3_EXECUTABLE ${PYTHON_EXECUTABLE})
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endif()
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else()
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find_package(Python3 3.6 COMPONENTS Interpreter QUIET)
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endif()
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# Use the Cython executable that lives next to the Python executable
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# if it is a local installation.
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if(Python3_EXECUTABLE)
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get_filename_component(_python_path ${Python3_EXECUTABLE} PATH)
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find_program(Cythonize_EXECUTABLE
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NAMES cythonize3 cythonize cythonize.bat
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HINTS ${_python_path})
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endif()
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include(FindPackageHandleStandardArgs)
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FIND_PACKAGE_HANDLE_STANDARD_ARGS(Cythonize REQUIRED_VARS Cythonize_EXECUTABLE)
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mark_as_advanced(Cythonize_EXECUTABLE)
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@ -50,6 +50,7 @@ function(check_for_autogen_files source_dir)
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file(GLOB SRC_AUTOGEN_FILES ${source_dir}/style_*.h)
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file(GLOB SRC_AUTOGEN_PACKAGES ${source_dir}/packages_*.h)
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list(APPEND SRC_AUTOGEN_FILES ${SRC_AUTOGEN_PACKAGES} ${source_dir}/lmpinstalledpkgs.h ${source_dir}/lmpgitversion.h)
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list(APPEND SRC_AUTOGEN_FILES ${SRC_AUTOGEN_PACKAGES} ${source_dir}/mliap_model_python_couple.h ${source_dir}/mliap_model_python_couple.cpp)
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foreach(_SRC ${SRC_AUTOGEN_FILES})
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get_filename_component(FILENAME "${_SRC}" NAME)
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if(EXISTS ${source_dir}/${FILENAME})
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31
cmake/Modules/Packages/MLIAP.cmake
Normal file
31
cmake/Modules/Packages/MLIAP.cmake
Normal file
@ -0,0 +1,31 @@
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# if PYTHON package is included we may also include Python support in MLIAP
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set(MLIAP_ENABLE_PYTHON_DEFAULT OFF)
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if(PKG_PYTHON)
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find_package(Cythonize)
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if(Cythonize_FOUND)
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set(MLIAP_ENABLE_PYTHON_DEFAULT ON)
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endif()
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endif()
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option(MLIAP_ENABLE_PYTHON "Build MLIAP package with Python support" ${MLIAP_ENABLE_PYTHON_DEFAULT})
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if(MLIAP_ENABLE_PYTHON)
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find_package(Cythonize REQUIRED)
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if(NOT PKG_PYTHON)
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message(FATAL_ERROR "Must enable PYTHON package for including Python support in MLIAP")
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endif()
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set(MLIAP_BINARY_DIR ${CMAKE_BINARY_DIR}/cython)
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set(MLIAP_CYTHON_SRC ${LAMMPS_SOURCE_DIR}/MLIAP/mliap_model_python_couple.pyx)
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get_filename_component(MLIAP_CYTHON_BASE ${MLIAP_CYTHON_SRC} NAME_WE)
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file(MAKE_DIRECTORY ${MLIAP_BINARY_DIR})
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add_custom_command(OUTPUT ${MLIAP_BINARY_DIR}/${MLIAP_CYTHON_BASE}.cpp ${MLIAP_BINARY_DIR}/${MLIAP_CYTHON_BASE}.h
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COMMAND ${CMAKE_COMMAND} -E copy_if_different ${MLIAP_CYTHON_SRC} ${MLIAP_BINARY_DIR}/${MLIAP_CYTHON_BASE}.pyx
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COMMAND ${Cythonize_EXECUTABLE} -3 ${MLIAP_BINARY_DIR}/${MLIAP_CYTHON_BASE}.pyx
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WORKING_DIRECTORY ${MLIAP_BINARY_DIR}
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MAIN_DEPENDENCY ${MLIAP_CYTHON_SRC}
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COMMENT "Generating C++ sources with cythonize...")
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target_compile_definitions(lammps PRIVATE -DMLIAP_PYTHON)
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target_sources(lammps PRIVATE ${MLIAP_BINARY_DIR}/${MLIAP_CYTHON_BASE}.cpp)
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target_include_directories(lammps PRIVATE ${MLIAP_BINARY_DIR})
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endif()
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@ -37,6 +37,7 @@ This is the list of packages that may require additional steps.
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* :ref:`KOKKOS <kokkos>`
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* :ref:`LATTE <latte>`
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* :ref:`MESSAGE <message>`
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* :ref:`MLIAP <mliap>`
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* :ref:`MSCG <mscg>`
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* :ref:`OPT <opt>`
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* :ref:`POEMS <poems>`
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@ -770,6 +771,54 @@ be installed on your system.
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----------
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.. _mliap:
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MLIAP package
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---------------------------
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Building the MLIAP package requires including the :ref:`SNAP <PKG-SNAP>`
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package. There will be an error message if this requirement is not satisfied.
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Using the *mliappy* model also requires enabling Python support, which
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in turn requires the :ref:`PYTHON <PKG-PYTHON>`
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package **and** requires you have the `cython <https://cython.org>`_ software
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installed and with it a working ``cythonize`` command. This feature requires
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compiling LAMMPS with Python version 3.6 or later.
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.. tabs::
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.. tab:: CMake build
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.. code-block:: bash
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-D MLIAP_ENABLE_PYTHON=value # enable mliappy model (default is autodetect)
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Without this setting, CMake will check whether it can find a
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suitable Python version and the ``cythonize`` command and choose
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the default accordingly. During the build procedure the provided
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.pyx file(s) will be automatically translated to C++ code and compiled.
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Please do **not** run ``cythonize`` manually in the ``src/MLIAP`` folder,
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as that can lead to compilation errors if Python support is not enabled.
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If you did by accident, please remove the generated .cpp and .h files.
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.. tab:: Traditional make
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The build uses the ``lib/python/Makefile.mliap_python`` file in the
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compile/link process to add a rule to update the files generated by
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the ``cythonize`` command in case the corresponding .pyx file(s) were
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modified. You may need to modify ``lib/python/Makefile.lammps``
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if the LAMMPS build fails.
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To manually enforce building MLIAP with Python support enabled,
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you can add
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``-DMLIAP_PYTHON`` to the ``LMP_INC`` variable in your machine makefile.
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You may have to manually run the ``cythonize`` command on .pyx file(s)
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in the ``src`` folder, if this is not automatically done during
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installing the MLIAP package. Please do **not** run ``cythonize``
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in the ``src/MLIAP`` folder, as that can lead to compilation errors
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if Python support is not enabled.
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If you did by accident, please remove the generated .cpp and .h files.
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----------
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.. _mscg:
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MSCG package
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@ -662,19 +662,31 @@ MLIAP package
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**Contents:**
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A general interface for machine-learning interatomic potentials.
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A general interface for machine-learning interatomic potentials, including PyTorch.
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**Install:**
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To use this package, also the :ref:`SNAP package <PKG-SNAP>` needs to be installed.
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To use this package, also the :ref:`SNAP package <PKG-SNAP>` package needs
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to be installed. To make the *mliappy* model available, also the
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:ref:`PYTHON package <PKG-PYTHON>` package needs to be installed, the version of
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Python must be 3.6 or later, and the `cython <https://cython.org/>`_ software
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must be installed.
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**Author:** Aidan Thompson (Sandia).
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**Author:** Aidan Thompson (Sandia), Nicholas Lubbers (LANL).
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**Supporting info:**
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* src/MLIAP: filenames -> commands
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* src/MLIAP/README
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* :doc:`pair_style mliap <pair_mliap>`
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* examples/mliap
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* :doc:`compute_style mliap <compute_mliap>`
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* examples/mliap (see README)
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When built with the *mliappy* model this package includes an extension for
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coupling with Python models, including PyTorch. In this case, the Python
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interpreter linked to LAMMPS will need the ``cython`` and ``numpy`` modules
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installed. The provided examples build models with PyTorch, which would
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therefore also needs to be installed to run those examples.
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----------
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@ -18,7 +18,7 @@ Syntax
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.. parsed-literal::
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*model* values = style
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style = *linear* or *quadratic*
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style = *linear* or *quadratic* or *mliappy*
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*descriptor* values = style filename
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style = *sna*
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filename = name of file containing descriptor definitions
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@ -56,13 +56,15 @@ and it is also straightforward to add new descriptor styles.
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The compute *mliap* command must be followed by two keywords
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*model* and *descriptor* in either order.
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The *model* keyword is followed by a model style, currently limited to
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either *linear* or *quadratic*.
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The *model* keyword is followed by the model style (*linear*, *quadratic* or *mliappy*).
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The *mliappy* model is only available
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if lammps is built with MLIAPPY package.
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The *descriptor* keyword is followed by a descriptor style, and additional arguments.
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Currently the only descriptor style is *sna*, indicating the bispectrum component
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descriptors used by the Spectral Neighbor Analysis Potential (SNAP) potentials of
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:doc:`pair_style snap <pair_snap>`.
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The compute currently supports just one descriptor style, but it is
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is straightforward to add new descriptor styles.
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The SNAP descriptor style *sna* is the same as that used by :doc:`pair_style snap <pair_snap>`,
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including the linear, quadratic, and chem variants.
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A single additional argument specifies the descriptor filename
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containing the parameters and setting used by the SNAP descriptor.
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The descriptor filename usually ends in the *.mliap.descriptor* extension.
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@ -162,9 +164,10 @@ potentials, see the examples in `FitSNAP <https://github.com/FitSNAP/FitSNAP>`_.
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Restrictions
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""""""""""""
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This compute is part of the MLIAP package. It is only enabled if
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LAMMPS was built with that package. In addition, building LAMMPS with the MLIAP package
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This compute is part of the MLIAP package. It is only enabled if LAMMPS
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was built with that package. In addition, building LAMMPS with the MLIAP package
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requires building LAMMPS with the SNAP package.
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The *mliappy* model requires building LAMMPS with the PYTHON package.
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See the :doc:`Build package <Build_package>` doc page for more info.
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Related commands
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@ -16,7 +16,7 @@ Syntax
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.. parsed-literal::
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*model* values = style filename
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style = *linear* or *quadratic*
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style = *linear* or *quadratic* or *mliappy*
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filename = name of file containing model definitions
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*descriptor* values = style filename
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style = *sna*
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@ -40,12 +40,15 @@ definitions of the interatomic potential functional form (*model*)
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and the geometric quantities that characterize the atomic positions
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(*descriptor*). By defining *model* and *descriptor* separately,
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it is possible to use many different models with a given descriptor,
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or many different descriptors with a given model. Currently, the pair_style
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supports just two models, *linear* and *quadratic*,
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and one descriptor, *sna*, the SNAP descriptor used by :doc:`pair_style snap <pair_snap>`, including the linear, quadratic,
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and chem variants. Work is currently underway to extend
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the interface to handle neural network energy models,
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and it is also straightforward to add new descriptor styles.
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or many different descriptors with a given model. The
|
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pair style currently supports just one descriptor style, but it is
|
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is straightforward to add new descriptor styles.
|
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The SNAP descriptor style *sna* is the same as that used by :doc:`pair_style snap <pair_snap>`,
|
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including the linear, quadratic, and chem variants.
|
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The available models are *linear*, *quadratic*, and *mliappy*.
|
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The *mliappy* style can be used to couple python models,
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e.g. PyTorch neural network energy models, and requires building
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LAMMPS with the PYTHON package (see below).
|
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In order to train a model, it is useful to know the gradient or derivative
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of energy, force, and stress w.r.t. model parameters. This information
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can be accessed using the related :doc:`compute mliap <compute_mliap>` command.
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@ -59,9 +62,8 @@ that specify the mapping of MLIAP
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element names to LAMMPS atom types,
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where N is the number of LAMMPS atom types.
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|
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The *model* keyword is followed by a model style, currently limited to
|
||||
either *linear* or *quadratic*. In both cases,
|
||||
this is followed by a single argument specifying the model filename containing the
|
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The *model* keyword is followed by the model style. This is followed
|
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by a single argument specifying the model filename containing the
|
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parameters for a set of elements.
|
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The model filename usually ends in the *.mliap.model* extension.
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It may contain parameters for many elements. The only requirement is that it
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@ -82,6 +84,16 @@ for the :doc:`pair_style snap <pair_snap>` coefficient file.
|
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Specifically, the line containing the element weight and radius is omitted,
|
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since these are handled by the *descriptor*.
|
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|
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Notes on mliappy models:
|
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When the *model* keyword is *mliappy*, the filename should end in '.pt',
|
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'.pth' for pytorch models, or be a pickle file. To load a model from
|
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memory (i.e. an existing python object), specify the filename as
|
||||
"LATER", and then call `lammps.mliap.load_model(model)` from python
|
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before using the pair style. When using lammps via the library mode, you will need to call
|
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`lammps.mliappy.activate_mliappy(lmp)` on the active lammps object
|
||||
before the pair style is defined. This call locates and loads the mliap-specific
|
||||
python module that is built into lammps.
|
||||
|
||||
The *descriptor* keyword is followed by a descriptor style, and additional arguments.
|
||||
Currently the only descriptor style is *sna*, indicating the bispectrum component
|
||||
descriptors used by the Spectral Neighbor Analysis Potential (SNAP) potentials of
|
||||
@ -138,11 +150,13 @@ This pair style can only be used via the *pair* keyword of the
|
||||
Restrictions
|
||||
""""""""""""
|
||||
|
||||
This style is part of the MLIAP package. It is only enabled if LAMMPS
|
||||
This pair style is part of the MLIAP package. It is only enabled if LAMMPS
|
||||
was built with that package. In addition, building LAMMPS with the MLIAP package
|
||||
requires building LAMMPS with the SNAP package.
|
||||
The *mliappy* model requires building LAMMPS with the PYTHON package.
|
||||
See the :doc:`Build package <Build_package>` doc page for more info.
|
||||
|
||||
|
||||
Related commands
|
||||
""""""""""""""""
|
||||
|
||||
|
||||
@ -558,6 +558,7 @@ Cygwin
|
||||
cylindrically
|
||||
Cyrot
|
||||
cyrstals
|
||||
cython
|
||||
Daivis
|
||||
Dammak
|
||||
dampflag
|
||||
|
||||
103
examples/mliap/README
Normal file
103
examples/mliap/README
Normal file
@ -0,0 +1,103 @@
|
||||
This directory contains multiple examples of
|
||||
machine-learning potentials defined using the
|
||||
MLIAP package in LAMMPS. The input files
|
||||
are described below.
|
||||
|
||||
in.mliap.snap.Ta06A
|
||||
-------------------
|
||||
Run linear SNAP, equivalent to examples/snap/in.snap.Ta06A
|
||||
|
||||
in.mliap.snap.WBe.PRB2019
|
||||
-------------------------
|
||||
Run linear SNAP, equivalent to examples/snap/in.snap.WBe.PRB2019
|
||||
|
||||
in.mliap.snap.quadratic
|
||||
-----------------------
|
||||
Run quadratic SNAP
|
||||
|
||||
in.mliap.snap.chem
|
||||
------------------
|
||||
Run EME-SNAP, equivalent to examples/snap/in.snap.InP.JCPA2020
|
||||
|
||||
in.mliap.snap.compute
|
||||
---------------------
|
||||
Generate the A matrix, the gradients (w.r.t. coefficients)
|
||||
of total potential energy, forces, and stress tensor for
|
||||
linear SNAP, equivalent to in.snap.compute
|
||||
|
||||
in.mliap.quadratic.compute
|
||||
--------------------------
|
||||
Generate the A matrix, the gradients (w.r.t. coefficients)
|
||||
of total potential energy, forces, and stress tensor for
|
||||
for quadratic SNAP, equivalent to in.snap.compute.quadratic
|
||||
|
||||
in.mliap.pytorch.Ta06A
|
||||
-----------------------
|
||||
This reproduces the output of in.mliap.snap.Ta06A above,
|
||||
but using the Python coupling to PyTorch.
|
||||
|
||||
This example can be run in two different ways:
|
||||
|
||||
1: Running a LAMMPS executable: in.mliap.pytorch.Ta06A
|
||||
|
||||
First run ``python convert_mliap_Ta06A.py``. It creates
|
||||
a PyTorch energy model that replicates the
|
||||
SNAP Ta06A potential and saves it in the file
|
||||
"Ta06A.mliap.pytorch.model.pt".
|
||||
|
||||
You can then run the example as follows
|
||||
|
||||
`lmp -in in.mliap.pytorch.Ta06A -echo both`
|
||||
|
||||
The resultant log.lammps output should be identical to that generated
|
||||
by in.mliap.snap.Ta06A.
|
||||
|
||||
If this fails, see the instructions for building the MLIAP package
|
||||
with Python support enabled. Also, confirm that the
|
||||
LAMMPS Python embedded Python interpreter is
|
||||
working by running ../examples/in.python.
|
||||
|
||||
2: Running a Python script: mliap_pytorch_Ta06A.py
|
||||
|
||||
Before testing this, ensure that the previous method
|
||||
(running a LAMMPS executable) works.
|
||||
|
||||
You can run the example in serial:
|
||||
|
||||
`python mliap_pytorch_Ta06A.py`
|
||||
|
||||
or in parallel:
|
||||
|
||||
`mpirun -np 4 python mliap_pytorch_Ta06A.py`
|
||||
|
||||
The resultant log.lammps output should be identical to that generated
|
||||
by in.mliap.snap.Ta06A and in.mliap.pytorch.Ta06A.
|
||||
|
||||
Not all Python installations support this mode of operation.
|
||||
It requires that the Python interpreter be initialized. If not,
|
||||
the script will exit with an error message.
|
||||
|
||||
in.mliap.pytorch.relu1hidden
|
||||
----------------------------
|
||||
This example demonstrates a simple neural network potential
|
||||
using PyTorch and SNAP descriptors.
|
||||
|
||||
`lmp -in in.mliap.pytorch.relu1hidden -echo both`
|
||||
|
||||
It was trained on just the energy component (no forces) of
|
||||
the data used in the original SNAP Ta06A potential for
|
||||
tantalum (Thompson, Swiler, Trott, Foiles, Tucker,
|
||||
J Comp Phys, 285, 316 (2015).). Because of the very small amount
|
||||
of energy training data, it uses just 1 hidden layer with
|
||||
a ReLU activation function. It is not expected to be
|
||||
very accurate for forces.
|
||||
|
||||
NOTE: Unlike the previous example, this example uses
|
||||
a pre-built PyTorch file `Ta06A.mliap.pytorch.model.pt`.
|
||||
It is read using `torch.load`,
|
||||
which implicitly uses the Python `pickle` module.
|
||||
This is known to be insecure. It is possible to construct malicious
|
||||
pickle data that will execute arbitrary code during unpickling. Never
|
||||
load data that could have come from an untrusted source, or that
|
||||
could have been tampered with. Only load data you trust.
|
||||
|
||||
18
examples/mliap/Ta06A.mliap.pytorch
Normal file
18
examples/mliap/Ta06A.mliap.pytorch
Normal file
@ -0,0 +1,18 @@
|
||||
# DATE: 2014-09-05 UNITS: metal CONTRIBUTOR: Aidan Thompson athomps@sandia.gov CITATION: Thompson, Swiler, Trott, Foiles and Tucker, arxiv.org, 1409.3880 (2014)
|
||||
|
||||
# Definition of SNAP potential Ta_Cand06A
|
||||
# Assumes 1 LAMMPS atom type
|
||||
|
||||
variable zblcutinner equal 4
|
||||
variable zblcutouter equal 4.8
|
||||
variable zblz equal 73
|
||||
|
||||
# Specify hybrid with SNAP, ZBL
|
||||
|
||||
pair_style hybrid/overlay &
|
||||
zbl ${zblcutinner} ${zblcutouter} &
|
||||
mliap model mliappy Ta06A.mliap.pytorch.model.pt &
|
||||
descriptor sna Ta06A.mliap.descriptor
|
||||
pair_coeff 1 1 zbl ${zblz} ${zblz}
|
||||
pair_coeff * * mliap Ta
|
||||
|
||||
26
examples/mliap/convert_mliap_Ta06A.py
Normal file
26
examples/mliap/convert_mliap_Ta06A.py
Normal file
@ -0,0 +1,26 @@
|
||||
import sys
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
# torch.nn.modules useful for defining a MLIAPPY model.
|
||||
from lammps.mliap.pytorch import TorchWrapper, IgnoreElems
|
||||
|
||||
# Read coefficients
|
||||
coeffs = np.genfromtxt("Ta06A.mliap.model",skip_header=6)
|
||||
|
||||
# Write coefficients to a pytorch linear model
|
||||
bias = coeffs[0]
|
||||
weights = coeffs[1:]
|
||||
lin = torch.nn.Linear(weights.shape[0],1)
|
||||
lin.to(torch.float64)
|
||||
with torch.autograd.no_grad():
|
||||
lin.weight.set_(torch.from_numpy(weights).unsqueeze(0))
|
||||
lin.bias.set_(torch.as_tensor(bias,dtype=torch.float64).unsqueeze(0))
|
||||
|
||||
# Wrap the pytorch model for usage with mliappy coupling.
|
||||
model = IgnoreElems(lin) # The linear module does not use the types.
|
||||
n_descriptors = lin.weight.shape[1]
|
||||
n_elements = 1
|
||||
linked_model = TorchWrapper(model,n_descriptors=n_descriptors,n_elements=n_elements)
|
||||
|
||||
torch.save(linked_model,"Ta06A.mliap.pytorch.model.pt")
|
||||
53
examples/mliap/in.mliap.pytorch.Ta06A
Normal file
53
examples/mliap/in.mliap.pytorch.Ta06A
Normal file
@ -0,0 +1,53 @@
|
||||
# Demonstrate MLIAP/PyTorch interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
variable nsteps index 100
|
||||
variable nrep equal 4
|
||||
variable a equal 3.316
|
||||
units metal
|
||||
|
||||
# generate the box and atom positions using a BCC lattice
|
||||
|
||||
variable nx equal ${nrep}
|
||||
variable ny equal ${nrep}
|
||||
variable nz equal ${nrep}
|
||||
|
||||
boundary p p p
|
||||
|
||||
lattice bcc $a
|
||||
region box block 0 ${nx} 0 ${ny} 0 ${nz}
|
||||
create_box 1 box
|
||||
create_atoms 1 box
|
||||
|
||||
mass 1 180.88
|
||||
|
||||
# choose potential
|
||||
|
||||
include Ta06A.mliap.pytorch
|
||||
|
||||
# Setup output
|
||||
|
||||
compute eatom all pe/atom
|
||||
compute energy all reduce sum c_eatom
|
||||
|
||||
compute satom all stress/atom NULL
|
||||
compute str all reduce sum c_satom[1] c_satom[2] c_satom[3]
|
||||
variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
|
||||
|
||||
thermo_style custom step temp epair c_energy etotal press v_press
|
||||
thermo 10
|
||||
thermo_modify norm yes
|
||||
|
||||
# Set up NVE run
|
||||
|
||||
timestep 0.5e-3
|
||||
neighbor 1.0 bin
|
||||
neigh_modify once no every 1 delay 0 check yes
|
||||
|
||||
# Run MD
|
||||
|
||||
velocity all create 300.0 4928459 loop geom
|
||||
fix 1 all nve
|
||||
run ${nsteps}
|
||||
|
||||
53
examples/mliap/in.mliap.pytorch.relu1hidden
Normal file
53
examples/mliap/in.mliap.pytorch.relu1hidden
Normal file
@ -0,0 +1,53 @@
|
||||
# Demonstrate MLIAP interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
variable nsteps index 100
|
||||
variable nrep equal 4
|
||||
variable a equal 3.316
|
||||
units metal
|
||||
|
||||
# generate the box and atom positions using a BCC lattice
|
||||
|
||||
variable nx equal ${nrep}
|
||||
variable ny equal ${nrep}
|
||||
variable nz equal ${nrep}
|
||||
|
||||
boundary p p p
|
||||
|
||||
lattice bcc $a
|
||||
region box block 0 ${nx} 0 ${ny} 0 ${nz}
|
||||
create_box 1 box
|
||||
create_atoms 1 box
|
||||
|
||||
mass 1 180.88
|
||||
|
||||
# choose potential
|
||||
|
||||
include relu1hidden.mliap.pytorch
|
||||
|
||||
# Setup output
|
||||
|
||||
compute eatom all pe/atom
|
||||
compute energy all reduce sum c_eatom
|
||||
|
||||
compute satom all stress/atom NULL
|
||||
compute str all reduce sum c_satom[1] c_satom[2] c_satom[3]
|
||||
variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
|
||||
|
||||
thermo_style custom step temp epair c_energy etotal press v_press
|
||||
thermo 10
|
||||
thermo_modify norm yes
|
||||
|
||||
# Set up NVE run
|
||||
|
||||
timestep 0.5e-3
|
||||
neighbor 1.0 bin
|
||||
neigh_modify once no every 1 delay 0 check yes
|
||||
|
||||
# Run MD
|
||||
|
||||
velocity all create 300.0 4928459 loop geom
|
||||
fix 1 all nve
|
||||
run ${nsteps}
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
# Demonstrate MLIAP interface to kinear SNAP potential
|
||||
# Demonstrate MLIAP interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
|
||||
157
examples/mliap/log.04Dec20.mliap.pytorch.Ta06A.g++.1
Normal file
157
examples/mliap/log.04Dec20.mliap.pytorch.Ta06A.g++.1
Normal file
@ -0,0 +1,157 @@
|
||||
LAMMPS (30 Nov 2020)
|
||||
using 48 OpenMP thread(s) per MPI task
|
||||
# Demonstrate MLIAP/PyTorch interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
variable nsteps index 100
|
||||
variable nrep equal 4
|
||||
variable a equal 3.316
|
||||
units metal
|
||||
|
||||
# generate the box and atom positions using a BCC lattice
|
||||
|
||||
variable nx equal ${nrep}
|
||||
variable nx equal 4
|
||||
variable ny equal ${nrep}
|
||||
variable ny equal 4
|
||||
variable nz equal ${nrep}
|
||||
variable nz equal 4
|
||||
|
||||
boundary p p p
|
||||
|
||||
lattice bcc $a
|
||||
lattice bcc 3.316
|
||||
Lattice spacing in x,y,z = 3.3160000 3.3160000 3.3160000
|
||||
region box block 0 ${nx} 0 ${ny} 0 ${nz}
|
||||
region box block 0 4 0 ${ny} 0 ${nz}
|
||||
region box block 0 4 0 4 0 ${nz}
|
||||
region box block 0 4 0 4 0 4
|
||||
create_box 1 box
|
||||
Created orthogonal box = (0.0000000 0.0000000 0.0000000) to (13.264000 13.264000 13.264000)
|
||||
1 by 1 by 1 MPI processor grid
|
||||
create_atoms 1 box
|
||||
Created 128 atoms
|
||||
create_atoms CPU = 0.002 seconds
|
||||
|
||||
mass 1 180.88
|
||||
|
||||
# choose potential
|
||||
|
||||
include Ta06A.mliap.pytorch
|
||||
# DATE: 2014-09-05 UNITS: metal CONTRIBUTOR: Aidan Thompson athomps@sandia.gov CITATION: Thompson, Swiler, Trott, Foiles and Tucker, arxiv.org, 1409.3880 (2014)
|
||||
|
||||
# Definition of SNAP potential Ta_Cand06A
|
||||
# Assumes 1 LAMMPS atom type
|
||||
|
||||
variable zblcutinner equal 4
|
||||
variable zblcutouter equal 4.8
|
||||
variable zblz equal 73
|
||||
|
||||
# Specify hybrid with SNAP, ZBL
|
||||
|
||||
pair_style hybrid/overlay zbl ${zblcutinner} ${zblcutouter} mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
pair_style hybrid/overlay zbl 4 ${zblcutouter} mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
pair_style hybrid/overlay zbl 4 4.8 mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
Loading python model complete.
|
||||
Reading potential file Ta06A.mliap.descriptor with DATE: 2014-09-05
|
||||
SNAP keyword rcutfac 4.67637
|
||||
SNAP keyword twojmax 6
|
||||
SNAP keyword nelems 1
|
||||
SNAP keyword elems Ta
|
||||
SNAP keyword radelems 0.5
|
||||
SNAP keyword welems 1
|
||||
SNAP keyword rfac0 0.99363
|
||||
SNAP keyword rmin0 0
|
||||
SNAP keyword bzeroflag 0
|
||||
pair_coeff 1 1 zbl ${zblz} ${zblz}
|
||||
pair_coeff 1 1 zbl 73 ${zblz}
|
||||
pair_coeff 1 1 zbl 73 73
|
||||
pair_coeff * * mliap Ta
|
||||
|
||||
|
||||
# Setup output
|
||||
|
||||
compute eatom all pe/atom
|
||||
compute energy all reduce sum c_eatom
|
||||
|
||||
compute satom all stress/atom NULL
|
||||
compute str all reduce sum c_satom[1] c_satom[2] c_satom[3]
|
||||
variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
|
||||
|
||||
thermo_style custom step temp epair c_energy etotal press v_press
|
||||
thermo 10
|
||||
thermo_modify norm yes
|
||||
|
||||
# Set up NVE run
|
||||
|
||||
timestep 0.5e-3
|
||||
neighbor 1.0 bin
|
||||
neigh_modify once no every 1 delay 0 check yes
|
||||
|
||||
# Run MD
|
||||
|
||||
velocity all create 300.0 4928459 loop geom
|
||||
fix 1 all nve
|
||||
run ${nsteps}
|
||||
run 100
|
||||
Neighbor list info ...
|
||||
update every 1 steps, delay 0 steps, check yes
|
||||
max neighbors/atom: 2000, page size: 100000
|
||||
master list distance cutoff = 5.8
|
||||
ghost atom cutoff = 5.8
|
||||
binsize = 2.9, bins = 5 5 5
|
||||
2 neighbor lists, perpetual/occasional/extra = 2 0 0
|
||||
(1) pair zbl, perpetual, half/full from (2)
|
||||
attributes: half, newton on
|
||||
pair build: halffull/newton
|
||||
stencil: none
|
||||
bin: none
|
||||
(2) pair mliap, perpetual
|
||||
attributes: full, newton on
|
||||
pair build: full/bin/atomonly
|
||||
stencil: full/bin/3d
|
||||
bin: standard
|
||||
Per MPI rank memory allocation (min/avg/max) = 159.8 | 159.8 | 159.8 Mbytes
|
||||
Step Temp E_pair c_energy TotEng Press v_press
|
||||
0 300 -11.85157 -11.85157 -11.813095 2717.1661 -2717.1661
|
||||
10 296.01467 -11.851059 -11.851059 -11.813095 2697.4796 -2697.4796
|
||||
20 284.53666 -11.849587 -11.849587 -11.813095 2289.1527 -2289.1527
|
||||
30 266.51577 -11.847275 -11.847275 -11.813095 1851.7131 -1851.7131
|
||||
40 243.05007 -11.844266 -11.844266 -11.813095 1570.684 -1570.684
|
||||
50 215.51032 -11.840734 -11.840734 -11.813094 1468.1899 -1468.1899
|
||||
60 185.48331 -11.836883 -11.836883 -11.813094 1524.8757 -1524.8757
|
||||
70 154.6736 -11.832931 -11.832931 -11.813094 1698.3351 -1698.3351
|
||||
80 124.79303 -11.829099 -11.829099 -11.813094 1947.0715 -1947.0715
|
||||
90 97.448054 -11.825592 -11.825592 -11.813094 2231.9563 -2231.9563
|
||||
100 74.035418 -11.822589 -11.822589 -11.813094 2515.8526 -2515.8526
|
||||
Loop time of 2.00236 on 48 procs for 100 steps with 128 atoms
|
||||
|
||||
Performance: 2.157 ns/day, 11.124 hours/ns, 49.941 timesteps/s
|
||||
288.8% CPU use with 1 MPI tasks x 48 OpenMP threads
|
||||
|
||||
MPI task timing breakdown:
|
||||
Section | min time | avg time | max time |%varavg| %total
|
||||
---------------------------------------------------------------
|
||||
Pair | 1.9998 | 1.9998 | 1.9998 | 0.0 | 99.87
|
||||
Neigh | 0 | 0 | 0 | 0.0 | 0.00
|
||||
Comm | 0.0011814 | 0.0011814 | 0.0011814 | 0.0 | 0.06
|
||||
Output | 0.00059724 | 0.00059724 | 0.00059724 | 0.0 | 0.03
|
||||
Modify | 0.00047352 | 0.00047352 | 0.00047352 | 0.0 | 0.02
|
||||
Other | | 0.0003468 | | | 0.02
|
||||
|
||||
Nlocal: 128.000 ave 128 max 128 min
|
||||
Histogram: 1 0 0 0 0 0 0 0 0 0
|
||||
Nghost: 727.000 ave 727 max 727 min
|
||||
Histogram: 1 0 0 0 0 0 0 0 0 0
|
||||
Neighs: 3712.00 ave 3712 max 3712 min
|
||||
Histogram: 1 0 0 0 0 0 0 0 0 0
|
||||
FullNghs: 7424.00 ave 7424 max 7424 min
|
||||
Histogram: 1 0 0 0 0 0 0 0 0 0
|
||||
|
||||
Total # of neighbors = 7424
|
||||
Ave neighs/atom = 58.000000
|
||||
Neighbor list builds = 0
|
||||
Dangerous builds = 0
|
||||
|
||||
Total wall time: 0:00:03
|
||||
157
examples/mliap/log.04Dec20.mliap.pytorch.Ta06A.g++.4
Normal file
157
examples/mliap/log.04Dec20.mliap.pytorch.Ta06A.g++.4
Normal file
@ -0,0 +1,157 @@
|
||||
LAMMPS (30 Nov 2020)
|
||||
using 48 OpenMP thread(s) per MPI task
|
||||
# Demonstrate MLIAP/PyTorch interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
variable nsteps index 100
|
||||
variable nrep equal 4
|
||||
variable a equal 3.316
|
||||
units metal
|
||||
|
||||
# generate the box and atom positions using a BCC lattice
|
||||
|
||||
variable nx equal ${nrep}
|
||||
variable nx equal 4
|
||||
variable ny equal ${nrep}
|
||||
variable ny equal 4
|
||||
variable nz equal ${nrep}
|
||||
variable nz equal 4
|
||||
|
||||
boundary p p p
|
||||
|
||||
lattice bcc $a
|
||||
lattice bcc 3.316
|
||||
Lattice spacing in x,y,z = 3.3160000 3.3160000 3.3160000
|
||||
region box block 0 ${nx} 0 ${ny} 0 ${nz}
|
||||
region box block 0 4 0 ${ny} 0 ${nz}
|
||||
region box block 0 4 0 4 0 ${nz}
|
||||
region box block 0 4 0 4 0 4
|
||||
create_box 1 box
|
||||
Created orthogonal box = (0.0000000 0.0000000 0.0000000) to (13.264000 13.264000 13.264000)
|
||||
1 by 2 by 2 MPI processor grid
|
||||
create_atoms 1 box
|
||||
Created 128 atoms
|
||||
create_atoms CPU = 0.002 seconds
|
||||
|
||||
mass 1 180.88
|
||||
|
||||
# choose potential
|
||||
|
||||
include Ta06A.mliap.pytorch
|
||||
# DATE: 2014-09-05 UNITS: metal CONTRIBUTOR: Aidan Thompson athomps@sandia.gov CITATION: Thompson, Swiler, Trott, Foiles and Tucker, arxiv.org, 1409.3880 (2014)
|
||||
|
||||
# Definition of SNAP potential Ta_Cand06A
|
||||
# Assumes 1 LAMMPS atom type
|
||||
|
||||
variable zblcutinner equal 4
|
||||
variable zblcutouter equal 4.8
|
||||
variable zblz equal 73
|
||||
|
||||
# Specify hybrid with SNAP, ZBL
|
||||
|
||||
pair_style hybrid/overlay zbl ${zblcutinner} ${zblcutouter} mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
pair_style hybrid/overlay zbl 4 ${zblcutouter} mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
pair_style hybrid/overlay zbl 4 4.8 mliap model mliappy Ta06A.mliap.pytorch.model.pkl descriptor sna Ta06A.mliap.descriptor
|
||||
Loading python model complete.
|
||||
Reading potential file Ta06A.mliap.descriptor with DATE: 2014-09-05
|
||||
SNAP keyword rcutfac 4.67637
|
||||
SNAP keyword twojmax 6
|
||||
SNAP keyword nelems 1
|
||||
SNAP keyword elems Ta
|
||||
SNAP keyword radelems 0.5
|
||||
SNAP keyword welems 1
|
||||
SNAP keyword rfac0 0.99363
|
||||
SNAP keyword rmin0 0
|
||||
SNAP keyword bzeroflag 0
|
||||
pair_coeff 1 1 zbl ${zblz} ${zblz}
|
||||
pair_coeff 1 1 zbl 73 ${zblz}
|
||||
pair_coeff 1 1 zbl 73 73
|
||||
pair_coeff * * mliap Ta
|
||||
|
||||
|
||||
# Setup output
|
||||
|
||||
compute eatom all pe/atom
|
||||
compute energy all reduce sum c_eatom
|
||||
|
||||
compute satom all stress/atom NULL
|
||||
compute str all reduce sum c_satom[1] c_satom[2] c_satom[3]
|
||||
variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
|
||||
|
||||
thermo_style custom step temp epair c_energy etotal press v_press
|
||||
thermo 10
|
||||
thermo_modify norm yes
|
||||
|
||||
# Set up NVE run
|
||||
|
||||
timestep 0.5e-3
|
||||
neighbor 1.0 bin
|
||||
neigh_modify once no every 1 delay 0 check yes
|
||||
|
||||
# Run MD
|
||||
|
||||
velocity all create 300.0 4928459 loop geom
|
||||
fix 1 all nve
|
||||
run ${nsteps}
|
||||
run 100
|
||||
Neighbor list info ...
|
||||
update every 1 steps, delay 0 steps, check yes
|
||||
max neighbors/atom: 2000, page size: 100000
|
||||
master list distance cutoff = 5.8
|
||||
ghost atom cutoff = 5.8
|
||||
binsize = 2.9, bins = 5 5 5
|
||||
2 neighbor lists, perpetual/occasional/extra = 2 0 0
|
||||
(1) pair zbl, perpetual, half/full from (2)
|
||||
attributes: half, newton on
|
||||
pair build: halffull/newton
|
||||
stencil: none
|
||||
bin: none
|
||||
(2) pair mliap, perpetual
|
||||
attributes: full, newton on
|
||||
pair build: full/bin/atomonly
|
||||
stencil: full/bin/3d
|
||||
bin: standard
|
||||
Per MPI rank memory allocation (min/avg/max) = 159.7 | 159.7 | 159.7 Mbytes
|
||||
Step Temp E_pair c_energy TotEng Press v_press
|
||||
0 300 -11.85157 -11.85157 -11.813095 2717.1661 -2717.1661
|
||||
10 296.01467 -11.851059 -11.851059 -11.813095 2697.4796 -2697.4796
|
||||
20 284.53666 -11.849587 -11.849587 -11.813095 2289.1527 -2289.1527
|
||||
30 266.51577 -11.847275 -11.847275 -11.813095 1851.7131 -1851.7131
|
||||
40 243.05007 -11.844266 -11.844266 -11.813095 1570.684 -1570.684
|
||||
50 215.51032 -11.840734 -11.840734 -11.813094 1468.1899 -1468.1899
|
||||
60 185.48331 -11.836883 -11.836883 -11.813094 1524.8757 -1524.8757
|
||||
70 154.6736 -11.832931 -11.832931 -11.813094 1698.3351 -1698.3351
|
||||
80 124.79303 -11.829099 -11.829099 -11.813094 1947.0715 -1947.0715
|
||||
90 97.448054 -11.825592 -11.825592 -11.813094 2231.9563 -2231.9563
|
||||
100 74.035418 -11.822589 -11.822589 -11.813094 2515.8526 -2515.8526
|
||||
Loop time of 0.562802 on 192 procs for 100 steps with 128 atoms
|
||||
|
||||
Performance: 7.676 ns/day, 3.127 hours/ns, 177.682 timesteps/s
|
||||
99.7% CPU use with 4 MPI tasks x 48 OpenMP threads
|
||||
|
||||
MPI task timing breakdown:
|
||||
Section | min time | avg time | max time |%varavg| %total
|
||||
---------------------------------------------------------------
|
||||
Pair | 0.53583 | 0.54622 | 0.55401 | 0.9 | 97.05
|
||||
Neigh | 0 | 0 | 0 | 0.0 | 0.00
|
||||
Comm | 0.0071442 | 0.01491 | 0.025289 | 5.4 | 2.65
|
||||
Output | 0.00092525 | 0.00095771 | 0.0010166 | 0.0 | 0.17
|
||||
Modify | 0.00014479 | 0.00015043 | 0.00015893 | 0.0 | 0.03
|
||||
Other | | 0.0005624 | | | 0.10
|
||||
|
||||
Nlocal: 32.0000 ave 32 max 32 min
|
||||
Histogram: 4 0 0 0 0 0 0 0 0 0
|
||||
Nghost: 431.000 ave 431 max 431 min
|
||||
Histogram: 4 0 0 0 0 0 0 0 0 0
|
||||
Neighs: 928.000 ave 928 max 928 min
|
||||
Histogram: 4 0 0 0 0 0 0 0 0 0
|
||||
FullNghs: 1856.00 ave 1856 max 1856 min
|
||||
Histogram: 4 0 0 0 0 0 0 0 0 0
|
||||
|
||||
Total # of neighbors = 7424
|
||||
Ave neighs/atom = 58.000000
|
||||
Neighbor list builds = 0
|
||||
Dangerous builds = 0
|
||||
|
||||
Total wall time: 0:00:02
|
||||
104
examples/mliap/mliap_pytorch_Ta06A.py
Normal file
104
examples/mliap/mliap_pytorch_Ta06A.py
Normal file
@ -0,0 +1,104 @@
|
||||
# Demonstrate how to load a model from the python side.
|
||||
# This is essentially the same as in.mliap.pytorch.Ta06A
|
||||
# except that python is the driving program, and lammps
|
||||
# is in library mode.
|
||||
|
||||
before_loading =\
|
||||
"""# Demonstrate MLIAP/PyTorch interface to linear SNAP potential
|
||||
|
||||
# Initialize simulation
|
||||
|
||||
variable nsteps index 100
|
||||
variable nrep equal 4
|
||||
variable a equal 3.316
|
||||
units metal
|
||||
|
||||
# generate the box and atom positions using a BCC lattice
|
||||
|
||||
variable nx equal ${nrep}
|
||||
variable ny equal ${nrep}
|
||||
variable nz equal ${nrep}
|
||||
|
||||
boundary p p p
|
||||
|
||||
lattice bcc $a
|
||||
region box block 0 ${nx} 0 ${ny} 0 ${nz}
|
||||
create_box 1 box
|
||||
create_atoms 1 box
|
||||
|
||||
mass 1 180.88
|
||||
|
||||
# choose potential
|
||||
|
||||
# DATE: 2014-09-05 UNITS: metal CONTRIBUTOR: Aidan Thompson athomps@sandia.gov CITATION: Thompson, Swiler, Trott, Foiles and Tucker, arxiv.org, 1409.3880 (2014)
|
||||
|
||||
# Definition of SNAP potential Ta_Cand06A
|
||||
# Assumes 1 LAMMPS atom type
|
||||
|
||||
variable zblcutinner equal 4
|
||||
variable zblcutouter equal 4.8
|
||||
variable zblz equal 73
|
||||
|
||||
# Specify hybrid with SNAP, ZBL
|
||||
|
||||
pair_style hybrid/overlay &
|
||||
zbl ${zblcutinner} ${zblcutouter} &
|
||||
mliap model mliappy LATER &
|
||||
descriptor sna Ta06A.mliap.descriptor
|
||||
pair_coeff 1 1 zbl ${zblz} ${zblz}
|
||||
pair_coeff * * mliap Ta
|
||||
"""
|
||||
after_loading =\
|
||||
"""
|
||||
|
||||
# Setup output
|
||||
|
||||
compute eatom all pe/atom
|
||||
compute energy all reduce sum c_eatom
|
||||
|
||||
compute satom all stress/atom NULL
|
||||
compute str all reduce sum c_satom[1] c_satom[2] c_satom[3]
|
||||
variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
|
||||
|
||||
thermo_style custom step temp epair c_energy etotal press v_press
|
||||
thermo 10
|
||||
thermo_modify norm yes
|
||||
|
||||
# Set up NVE run
|
||||
|
||||
timestep 0.5e-3
|
||||
neighbor 1.0 bin
|
||||
neigh_modify once no every 1 delay 0 check yes
|
||||
|
||||
# Run MD
|
||||
|
||||
velocity all create 300.0 4928459 loop geom
|
||||
fix 1 all nve
|
||||
run ${nsteps}
|
||||
"""
|
||||
|
||||
import lammps
|
||||
|
||||
lmp = lammps.lammps(cmdargs=['-echo','both'])
|
||||
|
||||
# Before defining the pair style, one must do the following:
|
||||
import lammps.mliap
|
||||
lammps.mliap.activate_mliappy(lmp)
|
||||
# Otherwise, when running lammps in library mode,
|
||||
# you will get an error:
|
||||
# "ERROR: Loading MLIAPPY coupling module failure."
|
||||
|
||||
# Setup the simulation and declare an empty model
|
||||
# by specifying model filename as "LATER"
|
||||
lmp.commands_string(before_loading)
|
||||
|
||||
# Define the model however you like. In this example
|
||||
# we load it from disk:
|
||||
import torch
|
||||
model = torch.load('Ta06A.mliap.pytorch.model.pt')
|
||||
|
||||
# Connect the PyTorch model to the mliap pair style.
|
||||
lammps.mliap.load_model(model)
|
||||
|
||||
# run the simulation with the mliap pair style
|
||||
lmp.commands_string(after_loading)
|
||||
18
examples/mliap/relu1hidden.mliap.pytorch
Normal file
18
examples/mliap/relu1hidden.mliap.pytorch
Normal file
@ -0,0 +1,18 @@
|
||||
# DATE: 2014-09-05 UNITS: metal CONTRIBUTOR: Aidan Thompson athomps@sandia.gov CITATION: Thompson, Swiler, Trott, Foiles and Tucker, arxiv.org, 1409.3880 (2014)
|
||||
|
||||
# Definition of SNAP potential Ta_Cand06A
|
||||
# Assumes 1 LAMMPS atom type
|
||||
|
||||
variable zblcutinner equal 4
|
||||
variable zblcutouter equal 4.8
|
||||
variable zblz equal 73
|
||||
|
||||
# Specify hybrid with SNAP, ZBL
|
||||
|
||||
pair_style hybrid/overlay &
|
||||
zbl ${zblcutinner} ${zblcutouter} &
|
||||
mliap model mliappy relu1hidden.mliap.pytorch.model.pt &
|
||||
descriptor sna Ta06A.mliap.descriptor
|
||||
pair_coeff 1 1 zbl ${zblz} ${zblz}
|
||||
pair_coeff * * mliap Ta
|
||||
|
||||
BIN
examples/mliap/relu1hidden.mliap.pytorch.model.pt
Normal file
BIN
examples/mliap/relu1hidden.mliap.pytorch.model.pt
Normal file
Binary file not shown.
3
lib/python/Makefile.mliap_python
Normal file
3
lib/python/Makefile.mliap_python
Normal file
@ -0,0 +1,3 @@
|
||||
|
||||
../mliap_model_python_couple.cpp: ../mliap_model_python_couple.pyx
|
||||
cythonize -3 ../mliap_model_python_couple.cpp
|
||||
@ -98,19 +98,23 @@ os.chdir(os.path.dirname(args.package))
|
||||
from distutils.core import setup
|
||||
from distutils.sysconfig import get_python_lib
|
||||
import site
|
||||
tryuser=False
|
||||
|
||||
try:
|
||||
sys.argv = ["setup.py","install"] # as if had run "python setup.py install"
|
||||
setup(name = "lammps",
|
||||
#Arguments common to global or user install -- everything but data_files
|
||||
setup_kwargs= dict(name="lammps",
|
||||
version=verstr,
|
||||
author="Steve Plimpton",
|
||||
author_email="sjplimp@sandia.gov",
|
||||
url="https://lammps.sandia.gov",
|
||||
description="LAMMPS Molecular Dynamics Python package",
|
||||
license="GPL",
|
||||
packages=['lammps'],
|
||||
data_files = [(os.path.join(get_python_lib(), 'lammps'), [args.lib])])
|
||||
packages=["lammps","lammps.mliap"],
|
||||
)
|
||||
|
||||
tryuser=False
|
||||
try:
|
||||
sys.argv = ["setup.py","install"] # as if had run "python setup.py install"
|
||||
setup_kwargs['data_files']=[(os.path.join(get_python_lib(), 'lammps'), [args.lib])]
|
||||
setup(**setup_kwargs)
|
||||
except:
|
||||
tryuser=True
|
||||
print ("Installation into global site-packages folder failed.\nTrying user folder %s now." % site.USER_SITE)
|
||||
@ -118,14 +122,7 @@ except:
|
||||
if tryuser:
|
||||
try:
|
||||
sys.argv = ["setup.py","install","--user"] # as if had run "python setup.py install --user"
|
||||
setup(name = "lammps",
|
||||
version = verstr,
|
||||
author = "Steve Plimpton",
|
||||
author_email = "sjplimp@sandia.gov",
|
||||
url = "https://lammps.sandia.gov",
|
||||
description = "LAMMPS Molecular Dynamics Python package",
|
||||
license = "GPL",
|
||||
packages=['lammps'],
|
||||
data_files = [(os.path.join(site.USER_SITE, 'lammps'), [args.lib])])
|
||||
setup_kwargs['data_files']=[(os.path.join(site.USER_SITE, 'lammps'), [args.lib])]
|
||||
setup(**setup_kwargs)
|
||||
except:
|
||||
print("Installation into user site package folder failed.")
|
||||
|
||||
13
python/lammps/mliap/__init__.py
Normal file
13
python/lammps/mliap/__init__.py
Normal file
@ -0,0 +1,13 @@
|
||||
|
||||
# Check compatiblity of this build with the python shared library.
|
||||
# If this fails, lammps will segfault because its library will
|
||||
# try to improperly start up a new interpreter.
|
||||
import sysconfig
|
||||
import ctypes
|
||||
library = sysconfig.get_config_vars('INSTSONAME')[0]
|
||||
pylib = ctypes.CDLL(library)
|
||||
if not pylib.Py_IsInitialized():
|
||||
raise RuntimeError("This interpreter is not compatible with python-based mliap for LAMMPS.")
|
||||
del sysconfig, ctypes, library, pylib
|
||||
|
||||
from .loader import load_model, activate_mliappy
|
||||
52
python/lammps/mliap/loader.py
Normal file
52
python/lammps/mliap/loader.py
Normal file
@ -0,0 +1,52 @@
|
||||
# ----------------------------------------------------------------------
|
||||
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
|
||||
# http://lammps.sandia.gov, Sandia National Laboratories
|
||||
# Steve Plimpton, sjplimp@sandia.gov
|
||||
#
|
||||
# Copyright (2003) Sandia Corporation. Under the terms of Contract
|
||||
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
|
||||
# certain rights in this software. This software is distributed under
|
||||
# the GNU General Public License.
|
||||
#
|
||||
# See the README file in the top-level LAMMPS directory.
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Contributing author: Nicholas Lubbers (LANL)
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
|
||||
import sys
|
||||
import importlib.util
|
||||
import importlib.machinery
|
||||
|
||||
def activate_mliappy(lmp):
|
||||
try:
|
||||
# Begin Importlib magic to find the embedded python module
|
||||
# This is needed because the filename for liblammps does not
|
||||
# match the spec for normal python modules, wherein
|
||||
# file names match with PyInit function names.
|
||||
# Also, python normally doesn't look for extensions besides '.so'
|
||||
# We fix both of these problems by providing an explict
|
||||
# path to the extension module 'mliap_model_python_couple' in
|
||||
|
||||
path = lmp.lib._name
|
||||
loader = importlib.machinery.ExtensionFileLoader('mliap_model_python_couple', path)
|
||||
spec = importlib.util.spec_from_loader('mliap_model_python_couple', loader)
|
||||
module = importlib.util.module_from_spec(spec)
|
||||
sys.modules['mliap_model_python_couple'] = module
|
||||
spec.loader.exec_module(module)
|
||||
# End Importlib magic to find the embedded python module
|
||||
|
||||
except Exception as ee:
|
||||
raise ImportError("Could not load MLIAP python coupling module.") from ee
|
||||
|
||||
def load_model(model):
|
||||
try:
|
||||
import mliap_model_python_couple
|
||||
except ImportError as ie:
|
||||
raise ImportError("MLIAP python module must be activated before loading\n"
|
||||
"the pair style. Call lammps.mliap.activate_mliappy(lmp)."
|
||||
) from ie
|
||||
mliap_model_python_couple.load_from_python(model)
|
||||
|
||||
65
python/lammps/mliap/pytorch.py
Normal file
65
python/lammps/mliap/pytorch.py
Normal file
@ -0,0 +1,65 @@
|
||||
# ----------------------------------------------------------------------
|
||||
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
|
||||
# http://lammps.sandia.gov, Sandia National Laboratories
|
||||
# Steve Plimpton, sjplimp@sandia.gov
|
||||
#
|
||||
# Copyright (2003) Sandia Corporation. Under the terms of Contract
|
||||
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
|
||||
# certain rights in this software. This software is distributed under
|
||||
# the GNU General Public License.
|
||||
#
|
||||
# See the README file in the top-level LAMMPS directory.
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Contributing author: Nicholas Lubbers (LANL)
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
def calc_n_params(model):
|
||||
return sum(p.nelement() for p in model.parameters())
|
||||
|
||||
class TorchWrapper(torch.nn.Module):
|
||||
def __init__(self, model,n_descriptors,n_elements,n_params=None,device=None,dtype=torch.float64):
|
||||
super().__init__()
|
||||
|
||||
self.model = model
|
||||
self.device = device
|
||||
self.dtype = dtype
|
||||
|
||||
# Put model on device and convert to dtype
|
||||
self.to(self.dtype)
|
||||
self.to(self.device)
|
||||
|
||||
if n_params is None:
|
||||
n_params = calc_n_params(model)
|
||||
|
||||
self.n_params = n_params
|
||||
self.n_descriptors = n_descriptors
|
||||
self.n_elements = n_elements
|
||||
|
||||
def forward(self, elems, bispectrum, beta, energy):
|
||||
|
||||
bispectrum = torch.from_numpy(bispectrum).to(dtype=self.dtype, device=self.device).requires_grad_(True)
|
||||
elems = torch.from_numpy(elems).to(dtype=torch.long, device=self.device) - 1
|
||||
|
||||
with torch.autograd.enable_grad():
|
||||
|
||||
energy_nn = self.model(bispectrum, elems)
|
||||
if energy_nn.ndim > 1:
|
||||
energy_nn = energy_nn.flatten()
|
||||
|
||||
beta_nn = torch.autograd.grad(energy_nn.sum(), bispectrum)[0]
|
||||
|
||||
beta[:] = beta_nn.detach().cpu().numpy().astype(np.float64)
|
||||
energy[:] = energy_nn.detach().cpu().numpy().astype(np.float64)
|
||||
|
||||
class IgnoreElems(torch.nn.Module):
|
||||
def __init__(self,subnet):
|
||||
super().__init__()
|
||||
self.subnet = subnet
|
||||
|
||||
def forward(self,bispectrum,elems):
|
||||
return self.subnet(bispectrum)
|
||||
@ -22,5 +22,5 @@ setup(
|
||||
url = "https://lammps.sandia.gov",
|
||||
description = "LAMMPS Molecular Dynamics Python package",
|
||||
license = "GPL",
|
||||
packages=["lammps"]
|
||||
packages=["lammps","lammps.mliap"],
|
||||
)
|
||||
|
||||
@ -106,6 +106,10 @@ if (test $1 = "PERI") then
|
||||
depend USER-OMP
|
||||
fi
|
||||
|
||||
if (test $1 = "PYTHON") then
|
||||
depend MLIAP
|
||||
fi
|
||||
|
||||
if (test $1 = "RIGID") then
|
||||
depend KOKKOS
|
||||
depend USER-OMP
|
||||
@ -114,6 +118,7 @@ fi
|
||||
|
||||
if (test $1 = "SNAP") then
|
||||
depend KOKKOS
|
||||
depend MLIAP
|
||||
fi
|
||||
|
||||
if (test $1 = "USER-CGSDK") then
|
||||
|
||||
67
src/MLIAP/Install.sh
Executable file
67
src/MLIAP/Install.sh
Executable file
@ -0,0 +1,67 @@
|
||||
# Install/unInstall package files in LAMMPS
|
||||
# mode = 0/1/2 for uninstall/install/update
|
||||
|
||||
mode=$1
|
||||
|
||||
# arg1 = file, arg2 = file it depends on
|
||||
|
||||
# enforce using portable C locale
|
||||
LC_ALL=C
|
||||
export LC_ALL
|
||||
|
||||
action () {
|
||||
if (test $mode = 0) then
|
||||
rm -f ../$1
|
||||
elif (! cmp -s $1 ../$1) then
|
||||
if (test -z "$2" || test -e ../$2) then
|
||||
cp $1 ..
|
||||
if (test $mode = 2) then
|
||||
echo " updating src/$1"
|
||||
fi
|
||||
fi
|
||||
elif (test -n "$2") then
|
||||
if (test ! -e ../$2) then
|
||||
rm -f ../$1
|
||||
fi
|
||||
fi
|
||||
}
|
||||
|
||||
# enforce package dependency
|
||||
if (test $1 = 1 || test $1 = 2) then
|
||||
if (test ! -e ../sna.h) then
|
||||
echo "Must install SNAP package to use MLIAP package"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
# all package files with no dependencies
|
||||
|
||||
for file in *.cpp *.h *.pyx; do
|
||||
test -f ${file} && action $file
|
||||
done
|
||||
|
||||
# edit 2 Makefile.package files to include/exclude package info
|
||||
|
||||
if (test $1 = 1) then
|
||||
if (test "$(type cythonize 2> /dev/null)" != "" && test -e ../python_impl.cpp) then
|
||||
if (test -e ../Makefile.package) then
|
||||
sed -i -e 's|^PKG_INC =[ \t]*|&-DMLIAP_PYTHON |' ../Makefile.package
|
||||
fi
|
||||
if (test -e ../Makefile.package.settings) then
|
||||
sed -i -e '/^include.*python.*mliap_python.*$/d' ../Makefile.package.settings
|
||||
# multiline form needed for BSD sed on Macs
|
||||
sed -i -e '4 i \
|
||||
include ..\/..\/lib\/python\/Makefile.mliap_python
|
||||
' ../Makefile.package.settings
|
||||
fi
|
||||
cythonize -3 ../mliap_model_python_couple.pyx
|
||||
fi
|
||||
|
||||
elif (test $1 = 0) then
|
||||
|
||||
if (test -e ../Makefile.package) then
|
||||
sed -i -e 's/[^ \t]*-DMLIAP_PYTHON[^ \t]* //g' ../Makefile.package
|
||||
fi
|
||||
rm -f ../mliap_model_python_couple.cpp ../mliap_model_python_couple.h
|
||||
sed -i -e '/^include.*python.*mliap_python.*$/d' ../Makefile.package.settings
|
||||
fi
|
||||
@ -8,12 +8,15 @@ definitions of the interatomic potential functional form (*model*)
|
||||
and the geometric quantities that characterize the atomic positions
|
||||
(*descriptor*). By defining *model* and *descriptor* separately,
|
||||
it is possible to use many different models with a given descriptor,
|
||||
or many different descriptors with a given model. Currently, the pair_style
|
||||
supports just two models, *linear* and *quadratic*,
|
||||
and one descriptor, *sna*, the SNAP descriptor, including the
|
||||
linear, quadratic, and chem variants. Work is currently underway to extend
|
||||
the interface to handle neural network energy models,
|
||||
and it is also straightforward to add new descriptor styles.
|
||||
or many different descriptors with a given model. The pair_style
|
||||
supports the following models: *linear*, *quadratic*, and
|
||||
*mliappy* (general Python interface to things like PyTorch, see below
|
||||
for build instructions).
|
||||
It currently supports only one class of descriptors,
|
||||
*sna*, the SNAP descriptors, including the
|
||||
linear, quadratic, and chem variants.
|
||||
It is straightforward to add new descriptor and model
|
||||
styles.
|
||||
|
||||
The mliap compute style provides gradients of the energy, force,
|
||||
and stress tensor w.r.t. model parameters.
|
||||
@ -27,4 +30,28 @@ reference potential.
|
||||
|
||||
To see how this command
|
||||
can be used within a Python workflow to train machine-learning interatomic
|
||||
potentials, see the examples in FitSNAP https://github.com/FitSNAP/FitSNAP>.
|
||||
potentials, see the examples in FitSNAP https://github.com/FitSNAP/FitSNAP.
|
||||
|
||||
*Additional instructions for building MLIAP with Python support enabled*
|
||||
|
||||
The *mliappy* energy model requires that the MLIAP package
|
||||
be compiled with Python support enabled.
|
||||
This extension, written by Nick Lubbers (LANL),
|
||||
provides a coupling to PyTorch and other Python modules.
|
||||
This should be automatically
|
||||
enabled by default if the prerequisite software is installed. It can be
|
||||
enforced during CMake configuration by setting the variable
|
||||
MLIAP_ENABLE_PYTHON=yes or for conventional build by adding -DMLIAP_PYTHON
|
||||
to the LMP_INC variable in your makefile and running the cythonize script
|
||||
on the .pyx file(s) copied to the src folder.
|
||||
|
||||
This requires to also install the PYTHON package and have the cython
|
||||
(https://cython.org) software installed. During configuration/compilation
|
||||
the cythonize script will be used to convert the provided .pyx file(s)
|
||||
to C++ code. Please do not run the cythonize script in the src/MLIAP folder.
|
||||
If you have done so by accident, you need to delete the generated .cpp and .h
|
||||
file(s) in the src/MLIAP folder or there may be problems during compilation.
|
||||
|
||||
More information on building LAMMPS with this package is here:
|
||||
|
||||
https://lammps.sandia.gov/doc/Build_extras.html#mliap
|
||||
|
||||
@ -11,12 +11,20 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include <cstring>
|
||||
|
||||
#include "mliap_data.h"
|
||||
#include "mliap_model_linear.h"
|
||||
#include "mliap_model_quadratic.h"
|
||||
#include "mliap_descriptor_snap.h"
|
||||
#ifdef MLIAP_PYTHON
|
||||
#include "mliap_model_python.h"
|
||||
#endif
|
||||
|
||||
#include "compute_mliap.h"
|
||||
#include "atom.h"
|
||||
#include "update.h"
|
||||
@ -65,7 +73,14 @@ ComputeMLIAP::ComputeMLIAP(LAMMPS *lmp, int narg, char **arg) :
|
||||
} else if (strcmp(arg[iarg+1],"quadratic") == 0) {
|
||||
model = new MLIAPModelQuadratic(lmp);
|
||||
iarg += 2;
|
||||
} else error->all(FLERR,"Illegal compute mliap command");
|
||||
}
|
||||
#ifdef MLIAP_PYTHON
|
||||
else if (strcmp(arg[iarg+1],"mliappy") == 0) {
|
||||
model = new MLIAPModelPython(lmp);
|
||||
iarg += 2;
|
||||
}
|
||||
#endif
|
||||
else error->all(FLERR,"Illegal compute mliap command");
|
||||
modelflag = 1;
|
||||
} else if (strcmp(arg[iarg],"descriptor") == 0) {
|
||||
if (iarg+2 > narg) error->all(FLERR,"Illegal compute mliap command");
|
||||
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_data.h"
|
||||
|
||||
#include "atom.h"
|
||||
@ -25,7 +29,8 @@ MLIAPData::MLIAPData(LAMMPS *lmp, int gradgradflag_in, int *map_in,
|
||||
class MLIAPModel* model_in,
|
||||
class MLIAPDescriptor* descriptor_in,
|
||||
class PairMLIAP* pairmliap_in) :
|
||||
Pointers(lmp), gradforce(nullptr), betas(nullptr), descriptors(nullptr), gamma(nullptr),
|
||||
Pointers(lmp), gradforce(nullptr), betas(nullptr),
|
||||
descriptors(nullptr), eatoms(nullptr), gamma(nullptr),
|
||||
gamma_row_index(nullptr), gamma_col_index(nullptr), egradient(nullptr),
|
||||
numneighs(nullptr), iatoms(nullptr), ielems(nullptr), jatoms(nullptr), jelems(nullptr),
|
||||
rij(nullptr), graddesc(nullptr), model(nullptr), descriptor(nullptr), list(nullptr)
|
||||
@ -64,6 +69,7 @@ MLIAPData::~MLIAPData()
|
||||
{
|
||||
memory->destroy(betas);
|
||||
memory->destroy(descriptors);
|
||||
memory->destroy(eatoms);
|
||||
memory->destroy(gamma_row_index);
|
||||
memory->destroy(gamma_col_index);
|
||||
memory->destroy(gamma);
|
||||
@ -133,6 +139,7 @@ void MLIAPData::generate_neighdata(NeighList* list_in, int eflag_in, int vflag_i
|
||||
if (natoms_max < natoms) {
|
||||
memory->grow(betas,natoms,ndescriptors,"MLIAPData:betas");
|
||||
memory->grow(descriptors,natoms,ndescriptors,"MLIAPData:descriptors");
|
||||
memory->grow(eatoms,natoms,"MLIAPData:eatoms");
|
||||
natoms_max = natoms;
|
||||
}
|
||||
|
||||
@ -267,6 +274,7 @@ double MLIAPData::memory_usage()
|
||||
|
||||
bytes += natoms*ndescriptors*sizeof(int); // betas
|
||||
bytes += natoms*ndescriptors*sizeof(int); // descriptors
|
||||
bytes += natoms*sizeof(double); // eatoms
|
||||
|
||||
bytes += natomneigh_max*sizeof(int); // iatoms
|
||||
bytes += natomneigh_max*sizeof(int); // ielems
|
||||
|
||||
@ -36,6 +36,8 @@ class MLIAPData : protected Pointers {
|
||||
double **gradforce;
|
||||
double** betas; // betas for all atoms in list
|
||||
double** descriptors; // descriptors for all atoms in list
|
||||
double* eatoms; // energies for all atoms in list
|
||||
double energy; // energy
|
||||
int ndescriptors; // number of descriptors
|
||||
int nparams; // number of model parameters per element
|
||||
int nelements; // number of elements
|
||||
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_descriptor.h"
|
||||
|
||||
using namespace LAMMPS_NS;
|
||||
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_descriptor_snap.h"
|
||||
|
||||
#include "atom.h"
|
||||
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_model.h"
|
||||
|
||||
#include "comm.h"
|
||||
@ -28,13 +32,9 @@ using namespace LAMMPS_NS;
|
||||
|
||||
MLIAPModel::MLIAPModel(LAMMPS* lmp, char* coefffilename) : Pointers(lmp)
|
||||
{
|
||||
coeffelem = nullptr;
|
||||
if (coefffilename) read_coeffs(coefffilename);
|
||||
else {
|
||||
nparams = 0;
|
||||
nelements = 0;
|
||||
ndescriptors = 0;
|
||||
}
|
||||
nonlinearflag = 0;
|
||||
}
|
||||
|
||||
@ -42,9 +42,9 @@ MLIAPModel::MLIAPModel(LAMMPS* lmp, char* coefffilename) : Pointers(lmp)
|
||||
|
||||
MLIAPModel::~MLIAPModel()
|
||||
{
|
||||
memory->destroy(coeffelem);
|
||||
}
|
||||
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
placeholder
|
||||
------------------------------------------------------------------------- */
|
||||
@ -73,7 +73,22 @@ void MLIAPModel::set_ndescriptors(int ndescriptors_in)
|
||||
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
void MLIAPModel::read_coeffs(char *coefffilename)
|
||||
|
||||
MLIAPModelSimple::MLIAPModelSimple(LAMMPS* lmp, char* coefffilename) : MLIAPModel(lmp, coefffilename)
|
||||
{
|
||||
coeffelem = nullptr;
|
||||
if (coefffilename) read_coeffs(coefffilename);
|
||||
}
|
||||
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
MLIAPModelSimple::~MLIAPModelSimple()
|
||||
{
|
||||
memory->destroy(coeffelem);
|
||||
}
|
||||
|
||||
|
||||
void MLIAPModelSimple::read_coeffs(char *coefffilename)
|
||||
{
|
||||
|
||||
// open coefficient file on proc 0
|
||||
@ -165,7 +180,7 @@ void MLIAPModel::read_coeffs(char *coefffilename)
|
||||
memory usage
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
double MLIAPModel::memory_usage()
|
||||
double MLIAPModelSimple::memory_usage()
|
||||
{
|
||||
double bytes = 0;
|
||||
|
||||
|
||||
@ -30,15 +30,26 @@ public:
|
||||
virtual void compute_gradgrads(class MLIAPData*)=0;
|
||||
virtual void compute_force_gradients(class MLIAPData*)=0;
|
||||
virtual void init();
|
||||
virtual double memory_usage();
|
||||
virtual double memory_usage()=0;
|
||||
int nelements; // # of unique elements
|
||||
int nonlinearflag; // 1 if gradient() requires escriptors
|
||||
int nonlinearflag; // 1 if gradient() requires descriptors
|
||||
int ndescriptors; // number of descriptors
|
||||
int nparams; // number of parameters per element
|
||||
|
||||
protected:
|
||||
void read_coeffs(char *);
|
||||
virtual void read_coeffs(char *)=0;
|
||||
};
|
||||
|
||||
class MLIAPModelSimple : public MLIAPModel {
|
||||
public:
|
||||
MLIAPModelSimple(LAMMPS*, char*);
|
||||
~MLIAPModelSimple();
|
||||
virtual double memory_usage();
|
||||
|
||||
protected:
|
||||
double **coeffelem; // element coefficients
|
||||
virtual void read_coeffs(char *);
|
||||
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_model_linear.h"
|
||||
#include "pair_mliap.h"
|
||||
#include "mliap_data.h"
|
||||
@ -21,7 +25,7 @@ using namespace LAMMPS_NS;
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
MLIAPModelLinear::MLIAPModelLinear(LAMMPS* lmp, char* coefffilename) :
|
||||
MLIAPModel(lmp, coefffilename)
|
||||
MLIAPModelSimple(lmp, coefffilename)
|
||||
{
|
||||
if (nparams > 0) ndescriptors = nparams - 1;
|
||||
}
|
||||
@ -51,8 +55,9 @@ int MLIAPModelLinear::get_nparams()
|
||||
|
||||
void MLIAPModelLinear::compute_gradients(MLIAPData* data)
|
||||
{
|
||||
data->energy = 0.0;
|
||||
|
||||
for (int ii = 0; ii < data->natoms; ii++) {
|
||||
const int i = data->iatoms[ii];
|
||||
const int ielem = data->ielems[ii];
|
||||
|
||||
double* coeffi = coeffelem[ielem];
|
||||
@ -74,7 +79,8 @@ void MLIAPModelLinear::compute_gradients(MLIAPData* data)
|
||||
for (int icoeff = 0; icoeff < data->ndescriptors; icoeff++)
|
||||
etmp += coeffi[icoeff+1]*data->descriptors[ii][icoeff];
|
||||
|
||||
data->pairmliap->e_tally(i,etmp);
|
||||
data->energy += etmp;
|
||||
data->eatoms[ii] = etmp;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@
|
||||
|
||||
namespace LAMMPS_NS {
|
||||
|
||||
class MLIAPModelLinear : public MLIAPModel {
|
||||
class MLIAPModelLinear : public MLIAPModelSimple {
|
||||
public:
|
||||
MLIAPModelLinear(LAMMPS*, char* = nullptr);
|
||||
~MLIAPModelLinear();
|
||||
|
||||
202
src/MLIAP/mliap_model_python.cpp
Normal file
202
src/MLIAP/mliap_model_python.cpp
Normal file
@ -0,0 +1,202 @@
|
||||
/* ----------------------------------------------------------------------
|
||||
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
|
||||
http://lammps.sandia.gov, Sandia National Laboratories
|
||||
Steve Plimpton, sjplimp@sandia.gov
|
||||
|
||||
Copyright (2003) Sandia Corporation. Under the terms of Contract
|
||||
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
|
||||
certain rights in this software. This software is distributed under
|
||||
the GNU General Public License.
|
||||
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Nicholas Lubbers (LANL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#ifdef MLIAP_PYTHON
|
||||
|
||||
#include <Python.h>
|
||||
#include "mliap_model_python.h"
|
||||
#include "mliap_model_python_couple.h"
|
||||
#include "pair_mliap.h"
|
||||
#include "mliap_data.h"
|
||||
#include "error.h"
|
||||
#include "utils.h"
|
||||
#include "lmppython.h"
|
||||
#include "python_compat.h"
|
||||
|
||||
|
||||
using namespace LAMMPS_NS;
|
||||
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
MLIAPModelPython::MLIAPModelPython(LAMMPS* lmp, char* coefffilename) :
|
||||
MLIAPModel(lmp, coefffilename)
|
||||
{
|
||||
model_loaded = 0;
|
||||
python->init();
|
||||
PyGILState_STATE gstate = PyGILState_Ensure();
|
||||
|
||||
PyObject * pyMain = PyImport_AddModule("__main__");
|
||||
|
||||
if (!pyMain) {
|
||||
PyGILState_Release(gstate);
|
||||
error->all(FLERR,"Could not initialize embedded Python");
|
||||
}
|
||||
|
||||
PyObject* coupling_module = PyImport_ImportModule("mliap_model_python_couple");
|
||||
|
||||
if (!coupling_module) {
|
||||
PyErr_Print();
|
||||
PyErr_Clear();
|
||||
PyGILState_Release(gstate);
|
||||
error->all(FLERR,"Loading MLIAPPY coupling module failure.");
|
||||
}
|
||||
// Recipe from lammps/src/pair_python.cpp :
|
||||
// add current directory to PYTHONPATH
|
||||
PyObject * py_path = PySys_GetObject((char *)"path");
|
||||
PyList_Append(py_path, PY_STRING_FROM_STRING("."));
|
||||
|
||||
// if LAMMPS_POTENTIALS environment variable is set, add it to PYTHONPATH as well
|
||||
const char * potentials_path = getenv("LAMMPS_POTENTIALS");
|
||||
if (potentials_path != NULL) {
|
||||
PyList_Append(py_path, PY_STRING_FROM_STRING(potentials_path));
|
||||
}
|
||||
PyGILState_Release(gstate);
|
||||
|
||||
if (coefffilename) read_coeffs(coefffilename);
|
||||
|
||||
nonlinearflag=1;
|
||||
}
|
||||
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
MLIAPModelPython::~MLIAPModelPython(){
|
||||
MLIAPPY_unload_model(this);
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
get number of parameters
|
||||
---------------------------------------------------------------------- */
|
||||
|
||||
|
||||
int MLIAPModelPython::get_nparams()
|
||||
{
|
||||
return nparams;
|
||||
}
|
||||
|
||||
void MLIAPModelPython::read_coeffs(char * fname)
|
||||
{
|
||||
PyGILState_STATE gstate = PyGILState_Ensure();
|
||||
|
||||
int loaded = MLIAPPY_load_model(this, fname);
|
||||
if (PyErr_Occurred()) {
|
||||
PyErr_Print();
|
||||
PyErr_Clear();
|
||||
PyGILState_Release(gstate);
|
||||
error->all(FLERR,"Loading python model failure.");
|
||||
}
|
||||
PyGILState_Release(gstate);
|
||||
|
||||
if (loaded) {
|
||||
this->connect_param_counts();
|
||||
}
|
||||
else {
|
||||
utils::logmesg(lmp,"Loading python model deferred.\n");
|
||||
}
|
||||
}
|
||||
|
||||
// Finalize loading of the model.
|
||||
void MLIAPModelPython::connect_param_counts()
|
||||
{
|
||||
PyGILState_STATE gstate = PyGILState_Ensure();
|
||||
nelements = MLIAPPY_nelements(this);
|
||||
nparams = MLIAPPY_nparams(this);
|
||||
ndescriptors = MLIAPPY_ndescriptors(this);
|
||||
|
||||
if (PyErr_Occurred()) {
|
||||
PyErr_Print();
|
||||
PyErr_Clear();
|
||||
PyGILState_Release(gstate);
|
||||
error->all(FLERR,"Loading python model failure.");
|
||||
}
|
||||
PyGILState_Release(gstate);
|
||||
model_loaded = 1;
|
||||
utils::logmesg(lmp,"Loading python model complete.\n");
|
||||
|
||||
}
|
||||
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Calculate model gradients w.r.t descriptors
|
||||
for each atom beta_i = dE(B_i)/dB_i
|
||||
---------------------------------------------------------------------- */
|
||||
|
||||
void MLIAPModelPython::compute_gradients(MLIAPData* data)
|
||||
{
|
||||
if (not model_loaded) {
|
||||
error->all(FLERR,"Model not loaded.");
|
||||
}
|
||||
|
||||
PyGILState_STATE gstate = PyGILState_Ensure();
|
||||
MLIAPPY_compute_gradients(this, data);
|
||||
if (PyErr_Occurred()) {
|
||||
PyErr_Print();
|
||||
PyErr_Clear();
|
||||
PyGILState_Release(gstate);
|
||||
error->all(FLERR,"Running python model failure.");
|
||||
}
|
||||
PyGILState_Release(gstate);
|
||||
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Calculate model double gradients w.r.t descriptors and parameters
|
||||
for each atom energy gamma_lk = d2E(B)/dB_k/dsigma_l,
|
||||
where sigma_l is a parameter, B_k a descriptor,
|
||||
and atom subscript i is omitted
|
||||
|
||||
gamma is in CSR format:
|
||||
nnz = number of non-zero values
|
||||
gamma_row_index[inz] = l indices, 0 <= l < nparams
|
||||
gamma_col_indexiinz] = k indices, 0 <= k < ndescriptors
|
||||
gamma[i][inz] = non-zero values, 0 <= inz < nnz
|
||||
|
||||
egradient is derivative of energy w.r.t. parameters
|
||||
---------------------------------------------------------------------- */
|
||||
|
||||
void MLIAPModelPython::compute_gradgrads(class MLIAPData* data)
|
||||
{
|
||||
error->all(FLERR,"compute_gradgrads not implemented");
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
calculate gradients of forces w.r.t. parameters
|
||||
egradient is derivative of energy w.r.t. parameters
|
||||
---------------------------------------------------------------------- */
|
||||
|
||||
void MLIAPModelPython::compute_force_gradients(class MLIAPData* data)
|
||||
{
|
||||
error->all(FLERR,"compute_force_gradients not implemented");
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
count the number of non-zero entries in gamma matrix
|
||||
---------------------------------------------------------------------- */
|
||||
|
||||
int MLIAPModelPython::get_gamma_nnz(class MLIAPData* data)
|
||||
{
|
||||
// todo: get_gamma_nnz
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
double MLIAPModelPython::memory_usage()
|
||||
{
|
||||
// todo: get approximate memory usage in coupling code.
|
||||
return 0;
|
||||
}
|
||||
|
||||
#endif
|
||||
47
src/MLIAP/mliap_model_python.h
Normal file
47
src/MLIAP/mliap_model_python.h
Normal file
@ -0,0 +1,47 @@
|
||||
/* -*- c++ -*- ----------------------------------------------------------
|
||||
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
|
||||
http://lammps.sandia.gov, Sandia National Laboratories
|
||||
Steve Plimpton, sjplimp@sandia.gov
|
||||
|
||||
Copyright (2003) Sandia Corporation. Under the terms of Contract
|
||||
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
|
||||
certain rights in this software. This software is distributed under
|
||||
the GNU General Public License.
|
||||
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#ifndef LMP_MLIAP_MODEL_PYTHON_H
|
||||
#define LMP_MLIAP_MODEL_PYTHON_H
|
||||
|
||||
#include "mliap_model.h"
|
||||
|
||||
namespace LAMMPS_NS {
|
||||
|
||||
|
||||
class MLIAPModelPython : public MLIAPModel {
|
||||
public:
|
||||
MLIAPModelPython(LAMMPS*, char* = NULL);
|
||||
~MLIAPModelPython();
|
||||
virtual int get_nparams();
|
||||
virtual int get_gamma_nnz(class MLIAPData*);
|
||||
virtual void compute_gradients(class MLIAPData*);
|
||||
virtual void compute_gradgrads(class MLIAPData*);
|
||||
virtual void compute_force_gradients(class MLIAPData*);
|
||||
virtual double memory_usage();
|
||||
void connect_param_counts(); // If possible convert this to protected/private and
|
||||
// and figure out how to declare cython fn
|
||||
// load_from_python as a friend.
|
||||
int model_loaded;
|
||||
|
||||
protected:
|
||||
virtual void read_coeffs(char *);
|
||||
|
||||
private:
|
||||
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
120
src/MLIAP/mliap_model_python_couple.pyx
Normal file
120
src/MLIAP/mliap_model_python_couple.pyx
Normal file
@ -0,0 +1,120 @@
|
||||
# cython: language_level=3
|
||||
# distutils: language = c++
|
||||
|
||||
cimport cython
|
||||
|
||||
import pickle
|
||||
|
||||
# For converting C arrays to numpy arrays
|
||||
import numpy as np
|
||||
|
||||
# For converting void * to integer for tracking object identity
|
||||
from libc.stdint cimport uintptr_t
|
||||
|
||||
from libcpp.string cimport string
|
||||
|
||||
|
||||
cdef extern from "mliap_data.h" namespace "LAMMPS_NS":
|
||||
cdef cppclass MLIAPData:
|
||||
# Array shapes
|
||||
int natoms
|
||||
int ndescriptors
|
||||
|
||||
# Input data
|
||||
int * ielems # types for all atoms in list
|
||||
double ** descriptors # descriptors for all atoms in list
|
||||
|
||||
# Output data to write to
|
||||
double ** betas # betas for all atoms in list
|
||||
double * eatoms # energy for all atoms in list
|
||||
double energy
|
||||
|
||||
cdef extern from "mliap_model_python.h" namespace "LAMMPS_NS":
|
||||
cdef cppclass MLIAPModelPython:
|
||||
void connect_param_counts()
|
||||
|
||||
|
||||
class MLIAPPYModelNotLinked(Exception): pass
|
||||
|
||||
|
||||
LOADED_MODELS = {}
|
||||
|
||||
cdef object c_id(MLIAPModelPython * c_model):
|
||||
"""
|
||||
Use python-style id of object to keep track of identity.
|
||||
Note, this is probably not a perfect general strategy but it should work fine with LAMMPS pair styles.
|
||||
"""
|
||||
return int(<uintptr_t> c_model)
|
||||
|
||||
cdef object retrieve(MLIAPModelPython * c_model) with gil:
|
||||
try:
|
||||
model = LOADED_MODELS[c_id(c_model)]
|
||||
except KeyError as ke:
|
||||
raise KeyError("Model has not been loaded.") from ke
|
||||
if model is None:
|
||||
raise MLIAPPYModelNotLinked("Model not linked, connect the model from the python side.")
|
||||
return model
|
||||
|
||||
cdef public int MLIAPPY_load_model(MLIAPModelPython * c_model, char* fname) with gil:
|
||||
str_fname = fname.decode('utf-8') # Python 3 only; not Python 2 not supported.
|
||||
if str_fname == "LATER":
|
||||
model = None
|
||||
returnval = 0
|
||||
else:
|
||||
if str_fname.endswith(".pt") or str_fname.endswith('.pth'):
|
||||
import torch
|
||||
model = torch.load(str_fname)
|
||||
else:
|
||||
with open(str_fname,'rb') as pfile:
|
||||
model = pickle.load(pfile)
|
||||
returnval = 1
|
||||
LOADED_MODELS[c_id(c_model)] = model
|
||||
return returnval
|
||||
|
||||
def load_from_python(model):
|
||||
unloaded_models = [k for k, v in LOADED_MODELS.items() if v is None]
|
||||
num_models = len(unloaded_models)
|
||||
cdef MLIAPModelPython * lmp_model
|
||||
|
||||
if num_models == 0:
|
||||
raise ValueError("No model in the waiting area.")
|
||||
elif num_models > 1:
|
||||
raise ValueError("Model is amibguous, more than one model in waiting area.")
|
||||
else:
|
||||
c_id = unloaded_models[0]
|
||||
LOADED_MODELS[c_id]=model
|
||||
lmp_model = <MLIAPModelPython *> <uintptr_t> c_id
|
||||
lmp_model.connect_param_counts()
|
||||
|
||||
|
||||
cdef public void MLIAPPY_unload_model(MLIAPModelPython * c_model) with gil:
|
||||
del LOADED_MODELS[c_id(c_model)]
|
||||
|
||||
cdef public int MLIAPPY_nparams(MLIAPModelPython * c_model) with gil:
|
||||
return int(retrieve(c_model).n_params)
|
||||
|
||||
cdef public int MLIAPPY_nelements(MLIAPModelPython * c_model) with gil:
|
||||
return int(retrieve(c_model).n_elements)
|
||||
|
||||
cdef public int MLIAPPY_ndescriptors(MLIAPModelPython * c_model) with gil:
|
||||
return int(retrieve(c_model).n_descriptors)
|
||||
|
||||
cdef public void MLIAPPY_compute_gradients(MLIAPModelPython * c_model, MLIAPData * data) with gil:
|
||||
model = retrieve(c_model)
|
||||
|
||||
n_d = data.ndescriptors
|
||||
n_a = data.natoms
|
||||
|
||||
# Make numpy arrays from pointers
|
||||
beta_np = np.asarray(<double[:n_a,:n_d] > &data.betas[0][0])
|
||||
desc_np = np.asarray(<double[:n_a,:n_d]> &data.descriptors[0][0])
|
||||
elem_np = np.asarray(<int[:n_a]> &data.ielems[0])
|
||||
en_np = np.asarray(<double[:n_a]> &data.eatoms[0])
|
||||
|
||||
# Invoke python model on numpy arrays.
|
||||
model(elem_np,desc_np,beta_np,en_np)
|
||||
|
||||
# Get the total energy from the atom energy.
|
||||
energy = np.sum(en_np)
|
||||
data.energy = <double> energy
|
||||
return
|
||||
@ -11,6 +11,10 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "mliap_model_quadratic.h"
|
||||
#include "pair_mliap.h"
|
||||
#include "mliap_data.h"
|
||||
@ -22,8 +26,9 @@ using namespace LAMMPS_NS;
|
||||
/* ---------------------------------------------------------------------- */
|
||||
|
||||
MLIAPModelQuadratic::MLIAPModelQuadratic(LAMMPS* lmp, char* coefffilename) :
|
||||
MLIAPModel(lmp, coefffilename)
|
||||
MLIAPModelSimple(lmp, coefffilename)
|
||||
{
|
||||
if (coefffilename) read_coeffs(coefffilename);
|
||||
if (nparams > 0) ndescriptors = sqrt(2*nparams)-1;
|
||||
nonlinearflag = 1;
|
||||
}
|
||||
@ -52,8 +57,9 @@ int MLIAPModelQuadratic::get_nparams()
|
||||
|
||||
void MLIAPModelQuadratic::compute_gradients(MLIAPData* data)
|
||||
{
|
||||
data->energy = 0.0;
|
||||
|
||||
for (int ii = 0; ii < data->natoms; ii++) {
|
||||
const int i = data->iatoms[ii];
|
||||
const int ielem = data->ielems[ii];
|
||||
|
||||
double* coeffi = coeffelem[ielem];
|
||||
@ -99,7 +105,8 @@ void MLIAPModelQuadratic::compute_gradients(MLIAPData* data)
|
||||
etmp += coeffi[k++]*bveci*bvecj;
|
||||
}
|
||||
}
|
||||
data->pairmliap->e_tally(i,etmp);
|
||||
data->energy += etmp;
|
||||
data->eatoms[ii] = etmp;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@
|
||||
|
||||
namespace LAMMPS_NS {
|
||||
|
||||
class MLIAPModelQuadratic : public MLIAPModel {
|
||||
class MLIAPModelQuadratic : public MLIAPModelSimple {
|
||||
public:
|
||||
MLIAPModelQuadratic(LAMMPS*, char* = nullptr);
|
||||
~MLIAPModelQuadratic();
|
||||
|
||||
@ -11,12 +11,19 @@
|
||||
See the README file in the top-level LAMMPS directory.
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
Contributing author: Aidan Thompson (SNL)
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
#include "pair_mliap.h"
|
||||
|
||||
#include "mliap_data.h"
|
||||
#include "mliap_model_linear.h"
|
||||
#include "mliap_model_quadratic.h"
|
||||
#include "mliap_descriptor_snap.h"
|
||||
#ifdef MLIAP_PYTHON
|
||||
#include "mliap_model_python.h"
|
||||
#endif
|
||||
|
||||
#include "atom.h"
|
||||
#include "error.h"
|
||||
@ -27,6 +34,7 @@
|
||||
|
||||
#include <cmath>
|
||||
#include <cstring>
|
||||
#include "error.h"
|
||||
|
||||
using namespace LAMMPS_NS;
|
||||
|
||||
@ -65,6 +73,17 @@ PairMLIAP::~PairMLIAP()
|
||||
|
||||
void PairMLIAP::compute(int eflag, int vflag)
|
||||
{
|
||||
|
||||
// consistency checks
|
||||
|
||||
if (data->ndescriptors != model->ndescriptors) {
|
||||
error->all(FLERR,"Incompatible model and descriptor descriptor count");
|
||||
};
|
||||
|
||||
if (data->nelements != model->nelements) {
|
||||
error->all(FLERR,"Incompatible model and descriptor element count");
|
||||
};
|
||||
|
||||
ev_init(eflag,vflag);
|
||||
|
||||
data->generate_neighdata(list, eflag, vflag);
|
||||
@ -78,6 +97,8 @@ void PairMLIAP::compute(int eflag, int vflag)
|
||||
|
||||
model->compute_gradients(data);
|
||||
|
||||
e_tally(data);
|
||||
|
||||
// calculate force contributions beta_i*dB_i/dR_j
|
||||
|
||||
descriptor->compute_forces(data);
|
||||
@ -107,6 +128,7 @@ void PairMLIAP::allocate()
|
||||
|
||||
void PairMLIAP::settings(int narg, char ** arg)
|
||||
{
|
||||
|
||||
if (narg < 4)
|
||||
error->all(FLERR,"Illegal pair_style command");
|
||||
|
||||
@ -130,6 +152,12 @@ void PairMLIAP::settings(int narg, char ** arg)
|
||||
if (iarg+3 > narg) error->all(FLERR,"Illegal pair_style mliap command");
|
||||
model = new MLIAPModelQuadratic(lmp,arg[iarg+2]);
|
||||
iarg += 3;
|
||||
#ifdef MLIAP_PYTHON
|
||||
} else if (strcmp(arg[iarg+1],"mliappy") == 0) {
|
||||
if (iarg+3 > narg) error->all(FLERR,"Illegal pair_style mliap command");
|
||||
model = new MLIAPModelPython(lmp,arg[iarg+2]);
|
||||
iarg += 3;
|
||||
#endif
|
||||
} else error->all(FLERR,"Illegal pair_style mliap command");
|
||||
modelflag = 1;
|
||||
} else if (strcmp(arg[iarg],"descriptor") == 0) {
|
||||
@ -211,22 +239,21 @@ void PairMLIAP::coeff(int narg, char **arg)
|
||||
data = new MLIAPData(lmp, gradgradflag, map, model, descriptor, this);
|
||||
data->init();
|
||||
|
||||
// consistency checks
|
||||
|
||||
if (data->ndescriptors != model->ndescriptors)
|
||||
error->all(FLERR,"Incompatible model and descriptor definitions");
|
||||
if (data->nelements != model->nelements)
|
||||
error->all(FLERR,"Incompatible model and descriptor definitions");
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
add energy of atom i to global and per-atom energy
|
||||
add energies to eng_vdwl and per-atom energy
|
||||
------------------------------------------------------------------------- */
|
||||
|
||||
void PairMLIAP::e_tally(int i, double ei)
|
||||
void PairMLIAP::e_tally(MLIAPData* data)
|
||||
{
|
||||
if (eflag_global) eng_vdwl += ei;
|
||||
if (eflag_atom) eatom[i] += ei;
|
||||
if (eflag_global) eng_vdwl += data->energy;
|
||||
if (eflag_atom)
|
||||
for (int ii = 0; ii < data->natoms; ii++) {
|
||||
const int i = data->iatoms[ii];
|
||||
eatom[i] += data->eatoms[ii];
|
||||
}
|
||||
}
|
||||
|
||||
/* ----------------------------------------------------------------------
|
||||
|
||||
@ -31,7 +31,7 @@ public:
|
||||
virtual void compute(int, int);
|
||||
void settings(int, char **);
|
||||
virtual void coeff(int, char **);
|
||||
void e_tally(int, double);
|
||||
void e_tally(class MLIAPData*);
|
||||
void v_tally(int, int, double*, double*);
|
||||
virtual void init_style();
|
||||
virtual double init_one(int, int);
|
||||
|
||||
@ -26,6 +26,14 @@
|
||||
#include <cstring>
|
||||
#include <Python.h> // IWYU pragma: export
|
||||
|
||||
#ifdef MLIAP_PYTHON
|
||||
#include "mliap_model_python.h"
|
||||
// The above should somehow really be included in the next file.
|
||||
// We could get around this with cython --capi-reexport-cincludes
|
||||
// However, that exposes -too many- headers.
|
||||
#include "mliap_model_python_couple.h"
|
||||
#endif
|
||||
|
||||
using namespace LAMMPS_NS;
|
||||
|
||||
enum{NONE,INT,DOUBLE,STRING,PTR};
|
||||
@ -47,11 +55,17 @@ PythonImpl::PythonImpl(LAMMPS *lmp) : Pointers(lmp)
|
||||
|
||||
nfunc = 0;
|
||||
pfuncs = nullptr;
|
||||
|
||||
// one-time initialization of Python interpreter
|
||||
// pyMain stores pointer to main module
|
||||
external_interpreter = Py_IsInitialized();
|
||||
|
||||
#ifdef MLIAP_PYTHON
|
||||
// Inform python intialization scheme of the mliappy module.
|
||||
// This -must- happen before python is initialized.
|
||||
int err = PyImport_AppendInittab("mliap_model_python_couple", PyInit_mliap_model_python_couple);
|
||||
if (err) error->all(FLERR,"Could not register MLIAPPY embedded python module.");
|
||||
#endif
|
||||
|
||||
Py_Initialize();
|
||||
|
||||
// only needed for Python 2.x and Python 3 < 3.7
|
||||
|
||||
@ -49,6 +49,8 @@ packages_ntopo.h
|
||||
# other auto-generated files
|
||||
lmpinstalledpkgs.h
|
||||
lmpgitversion.h
|
||||
mliap_model_python_couple.cpp
|
||||
mliap_model_python_couple.h
|
||||
# removed on 9 Sep 2020
|
||||
mergesort.h
|
||||
# renamed on 8 May 2020
|
||||
|
||||
Reference in New Issue
Block a user