# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Existing images: # --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.8 # --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.6 ARG CUDA_VERSION=11.1 #FROM ubuntu:20.04 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu18.04 ARG PYTHON_VERSION=3.8 ARG CONDA_VERSION=4.9.2 SHELL ["/bin/bash", "-c"] # https://techoverflow.net/2019/05/18/how-to-fix-configuring-tzdata-interactive-input-when-building-docker-images/ ENV \ PATH="$PATH:/root/.local/bin" \ DEBIAN_FRONTEND=noninteractive \ TZ=Europe/Prague \ # CUDA_TOOLKIT_ROOT_DIR="/usr/local/cuda" \ MKL_THREADING_LAYER=GNU RUN apt-get update -qq --fix-missing && \ apt-get install -y --no-install-recommends \ build-essential \ cmake \ git \ wget \ curl \ unzip \ ca-certificates \ libopenmpi-dev \ && \ # Install conda and python. # NOTE new Conda does not forward the exit status... https://github.com/conda/conda/issues/8385 curl -o ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-py38_${CONDA_VERSION}-Linux-x86_64.sh && \ chmod +x ~/miniconda.sh && \ ~/miniconda.sh -b && \ rm ~/miniconda.sh && \ # Cleaning apt-get autoremove -y && \ apt-get clean && \ rm -rf /root/.cache && \ rm -rf /var/lib/apt/lists/* ENV \ PATH="/root/miniconda3/bin:$PATH" \ LD_LIBRARY_PATH="/root/miniconda3/lib:$LD_LIBRARY_PATH" \ CUDA_TOOLKIT_ROOT_DIR="/usr/local/cuda" \ MKL_THREADING_LAYER=GNU \ MAKEFLAGS="-j$(nproc)" \ # MAKEFLAGS="-j1" \ TORCH_CUDA_ARCH_LIST="3.7;5.0;6.0;7.0;7.5" \ CONDA_ENV=lightning COPY environment.yml environment.yml ARG PYTORCH_VERSION=1.6 # conda init RUN conda update -n base -c defaults conda && \ conda create -y --name $CONDA_ENV python=${PYTHON_VERSION} pytorch=${PYTORCH_VERSION} cudatoolkit=${CUDA_VERSION} -c nvidia -c pytorch -c pytorch-test -c pytorch-nightly && \ conda init bash && \ # NOTE: this requires that the channel is presented in the yaml before packages # replace channel to nigtly if needed, fix PT version and remove Horovod as it will be installed later python -c "import re ; fname = 'environment.yml' ; req = re.sub(r'- python[>=]+[\d\.]+', '# - python=${PYTHON_VERSION}', open(fname).read()) ; open(fname, 'w').write(req)" && \ python -c "import re ; fname = 'environment.yml' ; req = re.sub(r'- pytorch[>=]+[\d\.]+', '# - pytorch=${PYTORCH_VERSION}', open(fname).read()) ; open(fname, 'w').write(req)" && \ cat environment.yml && \ conda env update --name $CONDA_ENV --file environment.yml && \ conda clean -ya && \ rm environment.yml ENV \ PATH=/root/miniconda3/envs/${CONDA_ENV}/bin:$PATH \ LD_LIBRARY_PATH="/root/miniconda3/envs/${CONDA_ENV}/lib:$LD_LIBRARY_PATH" \ # if you want this environment to be the default o \ne, uncomment the following line: CONDA_DEFAULT_ENV=${CONDA_ENV} \ HOROVOD_CUDA_HOME=$CUDA_TOOLKIT_ROOT_DIR \ HOROVOD_BUILD_CUDA_CC_LIST=$TORCH_CUDA_ARCH_LIST \ HOROVOD_GPU_OPERATIONS=NCCL \ HOROVOD_WITH_PYTORCH=1 \ HOROVOD_WITHOUT_TENSORFLOW=1 \ HOROVOD_WITHOUT_MXNET=1 \ HOROVOD_WITH_GLOO=1 \ HOROVOD_WITHOUT_MPI=1 COPY ./requirements/extra.txt requirements-extra.txt COPY ./requirements/examples.txt requirements-examples.txt COPY ./requirements/test.txt requirements-test.txt COPY ./requirements/adjust_versions.py requirements_adjust_versions.py RUN \ pip list | grep torch && \ python -c "import torch; print(torch.__version__)" && \ python requirements_adjust_versions.py requirements-extra.txt && \ python requirements_adjust_versions.py requirements-examples.txt && \ # Install remaining requirements pip install -r requirements-extra.txt --no-cache-dir && \ pip install -r requirements-examples.txt --no-cache-dir --find-links https://download.pytorch.org/whl/nightly/torch_nightly.html && \ pip install -r requirements-test.txt --no-cache-dir && \ rm requirements* RUN \ CUDA_VERSION_MAJOR=$(python -c "import torch ; print(torch.version.cuda.split('.')[0])") && \ py_ver=$(python -c "print(int('$PYTHON_VERSION'.split('.') >= '3.9'.split('.')))") && \ # install DALI, needed for examples # todo: waiting for 1.4 - https://github.com/NVIDIA/DALI/issues/3144#issuecomment-877386691 if [ $py_ver -eq "0" ]; then \ pip install --extra-index-url https://developer.download.nvidia.com/compute/redist "nvidia-dali-cuda${CUDA_VERSION_MAJOR}0>1.0" ; \ python -c 'from nvidia.dali.pipeline import Pipeline' ; \ fi RUN \ # install NVIDIA apex pip install --no-cache-dir --global-option="--cuda_ext" https://github.com/NVIDIA/apex/archive/refs/heads/master.zip && \ python -c "from apex import amp" RUN \ # Show what we have pip --version && \ conda info && \ pip list && \ python -c "import sys; ver = sys.version_info ; assert f'{ver.major}.{ver.minor}' == '$PYTHON_VERSION', ver" && \ python -c "from torch import __version__ as ver; assert '.'.join(ver.split('.')[:2]) == '$PYTORCH_VERSION', ver"