126 lines
4.8 KiB
Docker
126 lines
4.8 KiB
Docker
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Existing images:
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# --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.8
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# --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.6
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# --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.5
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# --build-arg PYTHON_VERSION=3.7 --build-arg PYTORCH_VERSION=1.4
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ARG CUDNN_VERSION=8
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ARG CUDA_VERSION=10.2
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# FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04
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FROM nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu18.04
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# FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu18.04
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ARG PYTHON_VERSION=3.7
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ARG PYTORCH_VERSION=1.6
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ARG CONDA_VERSION=4.9.2
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SHELL ["/bin/bash", "-c"]
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ENV PATH="$PATH:/root/.local/bin"
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RUN apt-get update -qq && \
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apt-get install -y --no-install-recommends \
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build-essential \
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cmake \
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git \
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wget \
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curl \
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unzip \
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ca-certificates \
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&& \
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# Install conda and python.
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# NOTE new Conda does not forward the exit status... https://github.com/conda/conda/issues/8385
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curl -o ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-py38_${CONDA_VERSION}-Linux-x86_64.sh && \
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chmod +x ~/miniconda.sh && \
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~/miniconda.sh -b && \
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rm ~/miniconda.sh && \
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# Cleaning
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apt-get autoremove -y && \
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apt-get clean && \
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rm -rf /root/.cache && \
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rm -rf /var/lib/apt/lists/*
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ENV \
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PATH="/root/miniconda3/bin:$PATH" \
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LD_LIBRARY_PATH="/root/miniconda3/lib:$LD_LIBRARY_PATH" \
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CUDA_TOOLKIT_ROOT_DIR="/usr/local/cuda" \
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MKL_THREADING_LAYER=GNU \
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HOROVOD_GPU_OPERATIONS=NCCL \
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HOROVOD_WITH_PYTORCH=1 \
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HOROVOD_WITHOUT_TENSORFLOW=1 \
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HOROVOD_WITHOUT_MXNET=1 \
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HOROVOD_WITH_GLOO=1 \
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HOROVOD_WITHOUT_MPI=1 \
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# MAKEFLAGS="-j$(nproc)" \
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MAKEFLAGS="-j1" \
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TORCH_CUDA_ARCH_LIST="3.7;5.0;6.0;7.0;7.5" \
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CONDA_ENV=lightning
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COPY environment.yml environment.yml
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# conda init
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RUN conda create -y --name $CONDA_ENV python=${PYTHON_VERSION} pytorch=${PYTORCH_VERSION} cudatoolkit=${CUDA_VERSION} -c pytorch -c pytorch-test -c pytorch-nightly && \
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conda init bash && \
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# NOTE: this requires that the channel is presented in the yaml before packages
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# replace channel to nigtly if needed, fix PT version and remove Horovod as it will be installed later
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python -c "import re ; fname = 'environment.yml' ; req = re.sub(r'- python[>=]+[\d\.]+', '# - python=${PYTHON_VERSION}', open(fname).read()) ; open(fname, 'w').write(req)" && \
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python -c "import re ; fname = 'environment.yml' ; req = re.sub(r'- pytorch[>=]+[\d\.]+', '# - pytorch=${PYTORCH_VERSION}', open(fname).read()) ; open(fname, 'w').write(req)" && \
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python -c "import re ; fname = 'environment.yml' ; req = re.sub(r'- horovod[>=]+[\d\.]+', '# - horovod', open(fname).read()) ; open(fname, 'w').write(req)" && \
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python -c "fname = 'environment.yml' ; req = open(fname).readlines() ; open(fname, 'w').writelines([ln for ln in req if 'horovod' not in ln])" && \
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cat environment.yml && \
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conda env update --name $CONDA_ENV --file environment.yml && \
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conda clean -ya && \
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rm environment.yml
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ENV \
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PATH /root/miniconda3/envs/${CONDA_ENV}/bin:$PATH \
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LD_LIBRARY_PATH="/root/miniconda3/envs/${CONDA_ENV}/lib:$LD_LIBRARY_PATH" \
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# if you want this environment to be the default one, uncomment the following line:
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CONDA_DEFAULT_ENV=${CONDA_ENV}
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COPY ./requirements/extra.txt requirements-extra.txt
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COPY ./requirements/test.txt requirements-test.txt
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RUN \
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pip list | grep torch && \
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python -c "import torch; print(torch.__version__)" && \
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# Install remaining requirements
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pip install -r requirements-extra.txt --no-cache-dir && \
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pip install -r requirements-test.txt --no-cache-dir && \
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rm requirements*
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RUN \
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# install DALI, needed for examples
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pip install --extra-index-url https://developer.download.nvidia.com/compute/redist nvidia-dali-cuda${CUDA_VERSION%%.*}0
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RUN \
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# install NVIDIA AMP
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git clone https://github.com/NVIDIA/apex && \
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pip install --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./apex && \
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rm -rf apex
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RUN \
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# Show what we have
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pip --version && \
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conda info && \
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pip list && \
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python -c "import sys; assert sys.version[:3] == '$PYTHON_VERSION', sys.version" && \
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python -c "import torch; assert torch.__version__[:3] == '$PYTORCH_VERSION', torch.__version__"
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