forked from HazyResearch/fly
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Dockerfile
135 lines (118 loc) · 5.8 KB
/
Dockerfile
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
# Inspired by https://github.com/anibali/docker-pytorch/blob/master/dockerfiles/1.10.0-cuda11.3-ubuntu20.04/Dockerfile
# ARG COMPAT=0
ARG PERSONAL=0
# FROM nvidia/cuda:11.3.1-devel-ubuntu20.04 as base-0
FROM nvcr.io/nvidia/pytorch:22.06-py3 as base
ENV HOST docker
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
# https://serverfault.com/questions/683605/docker-container-time-timezone-will-not-reflect-changes
ENV TZ America/Los_Angeles
RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
# git for installing dependencies
# tzdata to set time zone
# wget and unzip to download data
# [2021-09-09] TD: zsh, stow, subversion, fasd are for setting up my personal environment.
# [2021-12-07] TD: openmpi-bin for MPI (multi-node training)
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
curl \
ca-certificates \
sudo \
less \
htop \
git \
tzdata \
wget \
tmux \
zip \
unzip \
zsh stow subversion fasd \
&& rm -rf /var/lib/apt/lists/*
# openmpi-bin \
# Allow running runmpi as root
# ENV OMPI_ALLOW_RUN_AS_ROOT=1 OMPI_ALLOW_RUN_AS_ROOT_CONFIRM=1
# # Create a non-root user and switch to it
# RUN adduser --disabled-password --gecos '' --shell /bin/bash user \
# && echo "user ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/90-user
# USER user
# All users can use /home/user as their home directory
ENV HOME=/home/user
RUN mkdir -p /home/user && chmod 777 /home/user
WORKDIR /home/user
# https://stackoverflow.com/questions/43654656/dockerfile-if-else-condition-with-external-arguments
# FROM base-0 as base-1
# Use cuda-compat-11-3 package in case the driver is old. However, it doesn't work on A100.
# RUN apt-get install -y cuda-compat-11-3 && rm -rf /var/lib/apt/lists/*
# # https://docs.nvidia.com/deploy/cuda-compatibility/
# ENV LD_LIBRARY_PATH=/usr/local/cuda/compat:$LD_LIBRARY_PATH
# Set up personal environment
# FROM base-${COMPAT} as env-0
FROM base as env-0
FROM env-0 as env-1
# Use ONBUILD so that the dotfiles dir doesn't need to exist unless we're building a personal image
# https://stackoverflow.com/questions/31528384/conditional-copy-add-in-dockerfile
ONBUILD COPY dotfiles ./dotfiles
ONBUILD RUN cd ~/dotfiles && stow bash zsh tmux && sudo chsh -s /usr/bin/zsh $(whoami)
FROM env-${PERSONAL} as packages
# Need to put ARG in the build-stage where it is used, otherwise the ARG will be empty
# https://benkyriakou.com/posts/docker-args-empty
# https://github.com/distribution/distribution/issues/2459
ARG PYTHON_VERSION=3.8
# Install conda, python
# ENV PATH /home/user/conda/bin:$PATH
# RUN curl -o ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
# && chmod +x ~/miniconda.sh \
# && ~/miniconda.sh -b -p ~/conda \
# && rm ~/miniconda.sh \
# && conda install -y python=$PYTHON_VERSION \
# && conda clean -ya
# # Pytorch, scipy
# RUN conda install -y -c pytorch cudatoolkit=11.3 pytorch=1.10.1 torchvision torchtext \
# && conda install -y scipy \
# && conda clean -ya
# WORKDIR /opt/pytorch
# TD [2022-02-17] Trying to install a custom Pytorch version, but compilation (linking) fails.
# RUN git clone --depth 1 --branch v1.11.0-rc2 --recursive https://github.com/pytorch/pytorch \
# && rm -rf pytorch/.git && cp -r pytorch /opt/pytorch/ \
# && cd /opt/pytorch/pytorch \
# && CUDA_HOME="/usr/local/cuda" \
# CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
# NCCL_INCLUDE_DIR="/usr/include/" \
# NCCL_LIB_DIR="/usr/lib/" \
# USE_SYSTEM_NCCL=1 \
# USE_OPENCV=1 \
# pip install --no-cache-dir -v .
# Other libraries
# Disable pip cache: https://stackoverflow.com/questions/45594707/what-is-pips-no-cache-dir-good-for
ENV PIP_NO_CACHE_DIR=1
# # apex and pytorch-fast-transformers take a while to compile so we install them first
# TD [2022-04-28] apex is already installed. In case we need a newer commit:
# RUN pip install --upgrade --force-reinstall --global-option="--cpp_ext" --global-option="--cuda_ext" --global-option="--fast_multihead_attn" --global-option="--fmha" --global-option="--fast_layer_norm" --global-option="--xentropy" git+https://github.com/NVIDIA/apex.git#egg=apex
# TD [2021-10-28] pytorch-fast-transformers doesn't have a wheel compatible with CUDA 11.3 and Pytorch 1.10
# So we install from source, and change compiler flag -arch=compute_60 -> -arch=compute_70 for V100
# RUN pip install pytorch-fast-transformers==0.4.0
# RUN pip install git+git:https://github.com/idiap/[email protected] # doesn't work on V100
RUN git clone https://github.com/idiap/fast-transformers \
&& sed -i 's/\["-arch=compute_60"\]/\["-arch=compute_70"\]/' fast-transformers/setup.py \
&& pip install fast-transformers/ \
&& rm -rf fast-transformers
# xgboost conflicts with deepspeed
RUN pip uninstall -y xgboost && DS_BUILD_UTILS=1 DS_BUILD_FUSED_LAMB=1 pip install deepspeed==0.6.5
# General packages that we don't care about the version
# fs for reading tar files
RUN pip install pytest matplotlib jupyter ipython ipdb gpustat scikit-learn spacy munch einops fs fvcore gsutil cmake pykeops \
&& python -m spacy download en_core_web_sm
# hydra
RUN pip install hydra-core==1.2.0 hydra-colorlog==1.2.0 hydra-optuna-sweeper==1.2.0 python-dotenv rich
# Core packages
RUN pip install transformers==4.20.1 datasets==2.3.2 pytorch-lightning==1.6.5 triton==2.0.0.dev20220711 wandb==0.12.21 timm==0.6.5 torchmetrics==0.9.2
# For MLPerf
RUN pip install git+https://github.com/mlcommons/[email protected]
# This is for huggingface/examples and smyrf
RUN pip install tensorboard seqeval psutil sacrebleu rouge-score tensorflow_datasets h5py
# COPY applications/ applications
# RUN pip install applications/smyrf/forks/transformers/ \
# && pip install applications/smyrf/ \
# && rm -rf applications/
# ENV NVIDIA_REQUIRE_CUDA=cuda>=10.1