diff --git a/conda_enviroment.yml b/conda_enviroment.yml deleted file mode 100644 index 4786f5fdd7ba54f66784c8d9a8de050d6afcd440..0000000000000000000000000000000000000000 --- a/conda_enviroment.yml +++ /dev/null @@ -1,24 +0,0 @@ -FROM nvidia/cuda:10.1-devel-ubuntu18.04 - -RUN apt-get update --fix-missing && apt-get install -y build-essential wget git graphviz pandoc ffmpeg zip locales -RUN locale-gen en_US.UTF-8 -ENV LANG en_US.UTF-8 -ENV LANGUAGE en_US:en -ENV LC_ALL en_US.UTF-8 - -# --- Miniconda -RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \ - /bin/bash ~/miniconda.sh -b -p /opt/conda && \ - rm ~/miniconda.sh -ENV PATH /opt/conda/bin:$PATH - -# --- Install packages into conda using environment file -ADD conda_environment.yml -RUN conda update -n base conda && \ - conda env create -f conda_environment.yml - -# --- Disable gmpy backend of sympy, because of serialization bug -ENV MPMATH_NOGMPY=1 -ENV PATH /opt/conda/envs/pystencils_dev/bin/:$PATH - - diff --git a/conda_environment.yml b/conda_environment.yml new file mode 100644 index 0000000000000000000000000000000000000000..741c6b12df3af301796a4a922292606e882d47a1 --- /dev/null +++ b/conda_environment.yml @@ -0,0 +1,55 @@ +# Development environment with all dependencies to run tests and build documentation + +name: pystencils_machine_learning +channels: + - lssfau # for walberla package +dependencies: + # Basic dependencies: + - python >= 3.6 + - pip + - numpy + - sympy >= 1.1 + - appdirs # to find default cache directory on each platform + - joblib # caching on hard-disk, this is optional, but if not installed lbmpy is really slow + - jinja2 # for walberla kernel generation + - cython # speed up boundary list computation (optional) + # Display and postprocessing + - jupyter # a lot of documentation and tutorials are in notebook format + - matplotlib + - imageio + - pandas + - scipy + # Test suite dependencies + - pytest + - pytest-cov + - pytest-xdist + - flake8 + # Documentation dependencies + - sphinx + - sphinx_rtd_theme + - pandoc + # Other + - walberla # for distributed memory parallelization + - llvmlite # alternative jit backend + - gitpython # benchmarks reports include git hash + - psutil # for information about available / total RAM + - pip: + - islpy # used to optimize staggered kernels + - py-cpuinfo # get cpu info like cache sizes, supported vector instruction sets, ... + - graphviz # can show abstract syntax trees as formatted graphs + - ipy_table # HTML tables for jupyter notebooks + - pyevtk # VTK output for serial simulations + - blitzdb # file-based No-SQL database to store simulation results + - pycuda # run kernels on GPU (remove this if CUDA is not installed!) + - kerncraft # automatic performance analysis and benchmark + - influxdb # for reporting of benchmark results into time series database + - scikit-image # for phase field angle evaluations, when version 0.14.2 is available from conda it can be moved back + # Documentation + - nbsphinx # include notebooks into sphinx documentation + - sphinxcontrib-bibtex # add citations to sphinx doc + - sphinx_autodoc_typehints + # Machine learning dependencies + - pampy + - tqdm + - torch + - tensorflow-gpu diff --git a/machine_learning.Dockerfile b/machine_learning.Dockerfile index 6f352146ba9ff51529bf488837d42c44b7e899b4..ec0a6e63c5046eba87ed6a2f0317a251be80e985 100644 --- a/machine_learning.Dockerfile +++ b/machine_learning.Dockerfile @@ -13,9 +13,9 @@ RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86 ENV PATH /opt/conda/bin:$PATH # --- Install packages into conda using environment file -ADD conda_environment_dev.yml conda_environment_machine_learning.yml +ADD conda_environment.yml conda_environment.yml RUN conda update -n base conda && \ - conda env create -f conda_environment_machine_learning.yml + conda env create -f conda_environment.yml # --- Disable gmpy backend of sympy, because of serialization bug ENV MPMATH_NOGMPY=1