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Merge pull request #429 from Cytnx-dev/dev-master
merge dev-master
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‎.github/workflows/ci-cmake_pytests.yml‎

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name: Tests and Codecov
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on:
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workflow_dispatch:
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jobs:
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BuildAndTest:
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runs-on: ubuntu-latest
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defaults:
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run:
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shell: bash -l {0}
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steps:
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- uses: actions/checkout@v3
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- uses: conda-incubator/setup-miniconda@v2
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with:
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# Specify python version your environment will have. Remember to quote this, or
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# YAML will think you want python 3.1 not 3.10
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python-version: "3.11"
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# This uses *miniforge*, rather than *minicond*. The primary difference is that
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# the defaults channel is not enabled at all
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miniforge-version: latest
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# These properties enable the use of mamba, which is much faster and far less error
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# prone than conda while being completely compatible with the conda CLI
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use-mamba: true
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mamba-version: "*"
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- name: Install dependencies
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shell: bash -l {0}
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run: |
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mamba install _openmp_mutex=*=*_llvm cmake make boost git compilers numpy mkl mkl-include mkl-service pybind11 libblas=*=*mkl beartype
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mamba install gcovr gtest
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- name: CPU info
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shell: bash -l {0}
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run: lscpu
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- name: Configure CMake
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shell: bash -l {0}
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run: cmake -S ${{github.workspace}} -B ${{github.workspace}}/build -DCMAKE_INSTALL_PREFIX=/home/runner/work/Cytnx_lib -DUSE_MKL=on -DUSE_HPTT=on -DHPTT_ENABLE_FINE_TUNE=on -DHPTT_ENABLE_AVX=off -DBUILD_PYTHON=on -DCMAKE_EXPORT_COMPILE_COMMANDS=1 -DRUN_TESTS=on
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- name: Build
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shell: bash -l {0}
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working-directory: ${{github.workspace}}/build
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run: |
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cmake --version
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cmake --build . -j `nproc`
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- name: Install
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shell: bash -l {0}
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working-directory: ${{github.workspace}}/build
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run: |
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make install
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- name: Set python path
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run: |
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echo "PYTHONPATH=/home/runner/work/Cytnx_lib" >> $GITHUB_ENV
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- name: Test with pytest
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shell: bash -l {0}
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run: |
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pip install pytest pytest-cov
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pytest pytests/ --doctest-modules --junitxml=junit/test-results.xml --cov=com --cov-report=xml --cov-report=html
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# - name: Run CTest
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# shell: bash -l {0}
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# working-directory: ${{github.workspace}}/build
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# run: GTEST_COLOR=1 ctest --output-on-failure --output-junit junit.xml
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# - name: Run gcovr
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# shell: bash -l {0}
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# working-directory: ${{github.workspace}}/build
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# run: |
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# gcovr -r .. . --xml gcovr.xml -e ".*_deps.*$"
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# - name: Upload coverage to Codecov
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# uses: codecov/codecov-action@v3
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# with:
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# #token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
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# #directory: ${{runner.workspace}}/build
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# files: ${{github.workspace}}/build/gcovr.xml # optional
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# #working-directory: ${{runner.workspace}}/build
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# #root_dir: ${{runner.workspace}}
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# fail_ci_if_error: true # optional (default = false)
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# verbose: true # optional (default = false)
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# #version: "v0.1.15"
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#- name: Upload gcovr files
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# uses: actions/upload-artifact@v3
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# with:
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# name: CMakeError.log
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# path: /home/runner/work/Cytnx/Cytnx/build/CMakeFiles/CMakeError.log
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#- name: Upload junit files
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# uses: actions/upload-artifact@v3
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# with:
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# name: junit_xml
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# path: ${{github.workspace}}/build/junit.xml

‎.github/workflows/ci-cmake_tests.yml‎

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@@ -34,8 +34,9 @@ jobs:
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- name: Install dependencies
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shell: bash -l {0}
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run: |
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mamba install _openmp_mutex=*=*_llvm cmake make boost git compilers numpy mkl mkl-include mkl-service pybind11 libblas=*=*mkl
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mamba install _openmp_mutex=*=*_llvm cmake make boost git compilers numpy mkl mkl-include mkl-service pybind11 libblas=*=*mkl beartype
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mamba install gcovr gtest
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mamba install pytest pytest-cov
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- name: CPU info
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shell: bash -l {0}
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gcovr -r .. . --xml gcovr.xml -e ".*_deps.*$"
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v3
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uses: codecov/codecov-action@v4
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with:
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#token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
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token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
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#directory: ${{runner.workspace}}/build
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files: ${{github.workspace}}/build/gcovr.xml # optional
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#working-directory: ${{runner.workspace}}/build
@@ -75,6 +76,21 @@ jobs:
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verbose: true # optional (default = false)
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#version: "v0.1.15"
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- name: Install for python tests
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shell: bash -l {0}
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working-directory: ${{github.workspace}}/build
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run: |
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make install
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- name: Set python path
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shell: bash -l {0}
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run: |
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echo "PYTHONPATH=/home/runner/work/Cytnx_lib" >> $GITHUB_ENV
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- name: Test with pytest
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shell: bash -l {0}
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run: |
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pytest pytests/ --doctest-modules --junitxml=junit/test-results.xml --cov=com --cov-report=xml --cov-report=html
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#- name: Upload gcovr files
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# uses: actions/upload-artifact@v3
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# with:

‎CMakeLists.txt‎

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@@ -231,7 +231,9 @@ endif()
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# ## Python wrapper
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# #######
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IF(BUILD_PYTHON)
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find_package(PythonInterp REQUIRED)
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# PythonInterp is removed in newer version of cmake
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# find_package(PythonInterp REQUIRED)
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find_package (Python COMPONENTS Interpreter Development)
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find_package(pybind11 REQUIRED)
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if(NOT pybind11_FOUND)

‎Install.sh‎

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#=========================================================
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# [Note] Set the destination path for installation in Ins_dest
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#----------------------------------------------
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Ins_dest="/usr/local/cytnx"
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# Ins_dest="/usr/local/cytnx"
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Ins_dest="~/Cytnx_lib"
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FLAG="${FLAG} -DCMAKE_INSTALL_PREFIX=${Ins_dest}"
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#-----------------------------------------------
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# Please follow the guide from official mkl/oneMKL "post-installation" part
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# to source the proper setvars.sh and/or vars.sh
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#---------------------------
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FLAG="${FLAG} -DUSE_MKL=OFF"
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FLAG="${FLAG} -DUSE_MKL=ON"
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#---------------------------
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# 2-b) use OpenBLAS (DEFAULT = on (by settung DUSE_MKL=OFF above))
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# [Note] By default it will automatically find openblas installed
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#=========================================================
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# [Note] Wheather to run cytnx tests (DEFAULT = OFF)
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#-----------------------------------
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DRUN_TESTS=OFF
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DRUN_TESTS=ON
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FLAG="${FLAG} -DRUN_TESTS=${DRUN_TESTS}"
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#-----------------------------------
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# Build commands
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#=========================================================
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echo ${FLAG}
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# rm -rf build
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rm -rf build
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mkdir build
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cd build
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cmake ../ ${FLAG} #-DDEV_MODE=on
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make -j${nproc}
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make -j`nproc`
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make install
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#if DRUN_TESTS=ON, run tests
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shopt -s nocasematch
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case "${DRUN_TESTS}" in
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"ON" ) ctest; gcovr -r ../ . --html-details cov.html;;
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*) echo "Tests are skipped";;
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esac
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# if DRUN_TESTS=ON, run tests
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# ctest
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# shopt -s nocasematch
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# case "${DRUN_TESTS}" in
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# "ON" ) ctest; gcovr -r ../ . --html-details cov.html;;
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# *) echo "Tests are skipped";;
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# esac

‎cytnx/Network_conti.py‎

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from .utils import *
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from cytnx import *
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import imp
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try:
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imp.find_module('graphviz')
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from .NetGraph import *
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except ImportError:
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# import imp
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# try:
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# imp.find_module('graphviz')
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# from .NetGraph import *
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# except ImportError:
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# from .NetGraph_empty import *
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import importlib
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spec = importlib.util.find_spec("graphviz")
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if spec is None:
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# print("Can't find the graphviz module.")
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from .NetGraph_empty import *
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else:
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# If you chose to perform the actual import ...
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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# Adding the module to sys.modules is optional.
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#sys.modules["graphviz"] = module
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from .NetGraph import *
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import numpy as np
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‎example/Accessor/ex.cpp.out‎

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Total elem: 24
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type : Double (Float64)
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cytnx device: CPU
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Shape : (2,3,4)
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[[[0.00000e+00 1.00000e+00 2.00000e+00 3.00000e+00 ]
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[4.00000e+00 5.00000e+00 6.00000e+00 7.00000e+00 ]
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[8.00000e+00 9.00000e+00 1.00000e+01 1.10000e+01 ]]
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[[1.20000e+01 1.30000e+01 1.40000e+01 1.50000e+01 ]
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[1.60000e+01 1.70000e+01 1.80000e+01 1.90000e+01 ]
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[2.00000e+01 2.10000e+01 2.20000e+01 2.30000e+01 ]]]
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Total elem: 6
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type : Double (Float64)
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cytnx device: CPU
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Shape : (3,2)
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[[0.00000e+00 1.00000e+00 ]
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[4.00000e+00 5.00000e+00 ]
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[8.00000e+00 9.00000e+00 ]]

‎example/Accessor/example.cpp‎

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#include "cytnx.hpp"
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#include <iostream>
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using namespace cytnx;
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using namespace std;
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int main() {
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// 1. handy alias:
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typedef Accessor ac;
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/*
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2. Create a Tensor with
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shape (3,4,5),
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dtype =Type.Double [default],
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device=Device.cpu [default]
15+
*/
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Tensor A = cytnx::arange(24);
17+
A.reshape_({2, 3, 4});
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cout << A << endl;
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/*
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3. Accessing elements using accessor
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This is similar as python slices.
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-> A[0,:,0:2:1]
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*/
26+
Tensor B = A(0, ac::all(), ac::range(0, 2, 1));
27+
cout << B << endl;
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/* [Note] Conversion from python slice to ac:
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[::x] = ac::step(x)
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[a::x] = ac::tilend(a,x)
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[a::] = ac::tilend(a)
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[:b:] = ac::range(0,b,1)
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[a:b:x] = ac::range(a,b,x)
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*/
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37+
return 0;
38+
}

‎example/Accessor/example.cpp.out‎

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Total elem: 24
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type : Double (Float64)
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cytnx device: CPU
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Shape : (2,3,4)
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[[[0.00000e+00 1.00000e+00 2.00000e+00 3.00000e+00 ]
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[4.00000e+00 5.00000e+00 6.00000e+00 7.00000e+00 ]
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[8.00000e+00 9.00000e+00 1.00000e+01 1.10000e+01 ]]
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[[1.20000e+01 1.30000e+01 1.40000e+01 1.50000e+01 ]
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[1.60000e+01 1.70000e+01 1.80000e+01 1.90000e+01 ]
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[2.00000e+01 2.10000e+01 2.20000e+01 2.30000e+01 ]]]
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Total elem: 6
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type : Double (Float64)
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cytnx device: CPU
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Shape : (3,2)
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[[0.00000e+00 1.00000e+00 ]
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[4.00000e+00 5.00000e+00 ]
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[8.00000e+00 9.00000e+00 ]]

‎example/Accessor/example.py‎

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1+
import sys
2+
from pathlib import Path
3+
home = str(Path.home())
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sys.path.append(home + '/Cytnx_lib')
5+
from cytnx import *
6+
7+
A = arange(24);
8+
A.reshape_(2,3,4);
9+
print(A)
10+
11+
12+
B = A[0,:,0:2:1]
13+
print(B)

‎example/Accessor/example.py.out‎

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Total elem: 24
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type : Double (Float64)
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cytnx device: CPU
5+
Shape : (2,3,4)
6+
[[[0.00000e+00 1.00000e+00 2.00000e+00 3.00000e+00 ]
7+
[4.00000e+00 5.00000e+00 6.00000e+00 7.00000e+00 ]
8+
[8.00000e+00 9.00000e+00 1.00000e+01 1.10000e+01 ]]
9+
[[1.20000e+01 1.30000e+01 1.40000e+01 1.50000e+01 ]
10+
[1.60000e+01 1.70000e+01 1.80000e+01 1.90000e+01 ]
11+
[2.00000e+01 2.10000e+01 2.20000e+01 2.30000e+01 ]]]
12+
13+
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15+
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Total elem: 6
17+
type : Double (Float64)
18+
cytnx device: CPU
19+
Shape : (3,2)
20+
[[0.00000e+00 1.00000e+00 ]
21+
[4.00000e+00 5.00000e+00 ]
22+
[8.00000e+00 9.00000e+00 ]]

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