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Merge branch 'ko3n1g/build/pip' into 'main'
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build: Use multi-stage for parallel builds

See merge request ADLR/megatron-lm!2113
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ko3n1g committed Sep 20, 2024
2 parents 905de33 + 5c0697c commit c394f78
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74 changes: 35 additions & 39 deletions .gitlab/stages/01.tests.yml
Original file line number Diff line number Diff line change
Expand Up @@ -35,48 +35,44 @@ build_image:
variables:
STAGE: main
script:
- apk add bash
- |
set -x
env
eval "IMAGE=\$$IMAGE"
docker system prune -a --filter "until=24h" -f || true
if [[ "$CI_COMMIT_BRANCH" == "$CI_DEFAULT_BRANCH" ]]; then
ADDITIONAL_PARAMS="--pull"
fi
docker pull ${IMAGE}:${CI_PIPELINE_ID} || true
docker pull ${IMAGE}:${CI_MERGE_REQUEST_IID:-noop} || true
docker pull ${IMAGE}:buildcache || true
docker build \
--secret id=JET_INDEX_URLS \
--target $STAGE \
-f $FILE \
-t ${IMAGE}:${CI_PIPELINE_ID} \
-t ${IMAGE}:${CI_MERGE_REQUEST_IID:-noop} \
--build-arg CACHEBUST=$(cat /proc/sys/kernel/random/uuid) \
--cache-to type=inline \
--cache-from type=registry,ref=${IMAGE}:buildcache \
--cache-from type=registry,ref=${IMAGE}:${CI_PIPELINE_ID} \
--cache-from type=registry,ref=${IMAGE}:${CI_MERGE_REQUEST_IID:-noop} \
--build-arg FROM_IMAGE_NAME=$BASE_IMAGE \
${ADDITIONAL_PARAMS} .
docker push ${IMAGE}:${CI_PIPELINE_ID}
docker push ${IMAGE}:${CI_MERGE_REQUEST_IID:-noop}
if [[ "$CI_COMMIT_BRANCH" == "ci-nightly-a100" ]]; then
docker tag ${IMAGE}:${CI_PIPELINE_ID} ${IMAGE}:nightly
docker push ${IMAGE}:nightly
fi
bash -c '
set -x
env
eval "IMAGE=\$$IMAGE"
docker system prune -a --filter "until=24h" -f || true
docker buildx create --name container --driver=docker-container
ADDITIONAL_PARAMS=()
if [[ "$CI_COMMIT_BRANCH" == "$CI_DEFAULT_BRANCH" ]]; then
ADDITIONAL_PARAMS+=("--pull")
ADDITIONAL_PARAMS+=("--cache-to type=registry,ref=${IMAGE}-buildcache:main")
fi
if [[ "$CI_COMMIT_BRANCH" == "$CI_DEFAULT_BRANCH" ]]; then
docker tag ${IMAGE}:${CI_PIPELINE_ID} ${IMAGE}:buildcache
docker push ${IMAGE}:buildcache
fi
if [[ "$CI_COMMIT_BRANCH" == "ci-nightly-a100" ]]; then
ADDITIONAL_PARAMS+=("-t ${IMAGE}:nightly")
fi
DOCKER_BUILDKIT=1 docker build \
--secret id=JET_INDEX_URLS \
--target $STAGE \
-f $FILE \
-t ${IMAGE}:${CI_PIPELINE_ID} \
--builder=container \
--build-arg CACHEBUST=$(cat /proc/sys/kernel/random/uuid) \
--cache-to type=registry,ref=${IMAGE}-buildcache:${CI_PIPELINE_ID} \
--cache-to type=registry,ref=${IMAGE}-buildcache:${CI_MERGE_REQUEST_IID:-noop} \
--cache-from type=registry,ref=${IMAGE}-buildcache:main \
--cache-from type=registry,ref=${IMAGE}-buildcache:${CI_PIPELINE_ID} \
--cache-from type=registry,ref=${IMAGE}-buildcache:${CI_MERGE_REQUEST_IID:-noop} \
--build-arg FROM_IMAGE_NAME=$BASE_IMAGE \
--push \
${ADDITIONAL_PARAMS[@]} .
'
retry:
max: 2

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118 changes: 45 additions & 73 deletions Dockerfile.ci
Original file line number Diff line number Diff line change
@@ -1,82 +1,54 @@
# syntax=docker/dockerfile:experimental
# syntax=docker/dockerfile:1.3-labs

ARG FROM_IMAGE_NAME
FROM $FROM_IMAGE_NAME as main
ENV DEBIAN_FRONTEND=noninteractive

RUN sed -i -e 's/^APT/# APT/' -e 's/^DPkg/# DPkg/' \
/etc/apt/apt.conf.d/docker-clean

RUN apt-get update && \
apt-get install -y --no-install-recommends gettext && \
apt-get clean

RUN wget https://github.com/mikefarah/yq/releases/download/v4.44.1/yq_linux_amd64 -O /usr/local/bin/yq && \
chmod a+x /usr/local/bin/yq

##### For Mamba begin #####
RUN pip uninstall -y triton && \
pip install triton==2.1.0
FROM $FROM_IMAGE_NAME as build_causal_conv1d
WORKDIR /opt
RUN CAUSAL_CONV1D_FORCE_BUILD=TRUE pip3 wheel -v git+https://github.com/Dao-AILab/[email protected]

# The causal-conv1d and mamba-ssm packages below are built from scratch here
# (which takes significant time) because there are no wheels available on PyPI
# for these relatively newer versions of the packages that are compatible with
# the older NGC-variant PyTorch version (e.g. version 2.2.0.dev231106) that we
# are using (in the NGC base container). Generally, if the package is not
# compatible with the PyTorch version, then it will generate a Python import
# error. The package authors tend to only release wheels for new versions of
# these pacakges which are compatible with the versions of regular PyTorch and
# NGC-variant PyTorch that are newer at the time of release. So, to use newer
# versions of these packages with relatively older versions of the NGC PyTorch
# container, we tend to have to build the packages from scratch.
FROM $FROM_IMAGE_NAME as build_grouped_gemm
WORKDIR /opt
RUN pip3 wheel -v git+https://github.com/fanshiqing/[email protected]

RUN cd /tmp && \
pip uninstall -y causal-conv1d && \
git clone https://github.com/Dao-AILab/causal-conv1d.git && \
cd causal-conv1d && \
git checkout v1.2.2.post1 && \
CAUSAL_CONV1D_FORCE_BUILD=TRUE pip install . && \
cd .. && \
rm -rf causal-conv1d
FROM $FROM_IMAGE_NAME as build_mamba_ssm
WORKDIR /opt
RUN MAMBA_FORCE_BUILD=TRUE pip3 wheel -v git+https://github.com/state-spaces/[email protected]

RUN cd /tmp && \
pip uninstall -y mamba-ssm && \
git clone https://github.com/state-spaces/mamba.git && \
cd mamba && \
git checkout v2.0.3 && \
MAMBA_FORCE_BUILD=TRUE pip install . && \
cd .. && \
rm -rf mamba
##### For Mamba end #####

##### For JET-API start #####
RUN apt-get update && \
apt-get install -y python3-venv && \
apt-get clean -y && \
python -m venv /opt/jet
##### For JET-API end #####

RUN pip3 install --no-cache-dir \
einops \
flask-restful \
nltk \
pytest \
pytest-cov \
pytest_mock \
pytest-random-order \
sentencepiece \
wrapt \
git+https://github.com/fanshiqing/[email protected] \
zarr \
tensorstore==0.1.45 \
wandb

COPY . /workspace/megatron-lm

COPY . /workspace/megatron-lm
RUN cp -r /workspace/megatron-lm /opt && \
pip install /opt/megatron-lm
FROM $FROM_IMAGE_NAME as main
ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && \
apt-get install -y --no-install-recommends gettext python3-venv && \
apt-get clean && \
python -m venv /opt/jet && \
wget https://github.com/mikefarah/yq/releases/download/v4.44.1/yq_linux_amd64 -O /usr/local/bin/yq && \
chmod a+x /usr/local/bin/yq

COPY --from=build_causal_conv1d /opt/causal_conv1d-1.2.2.post1-cp310-cp310-linux_x86_64.whl ./
COPY --from=build_grouped_gemm /opt/grouped_gemm-1.1.2-cp310-cp310-linux_x86_64.whl ./
COPY --from=build_mamba_ssm /opt/mamba_ssm-2.0.3-cp310-cp310-linux_x86_64.whl ./

RUN pip3 install --no-cache-dir --upgrade-strategy only-if-needed -v \
einops \
flask-restful \
nltk \
pytest \
pytest-cov \
pytest_mock \
pytest-random-order \
sentencepiece \
wrapt \
zarr \
wandb \
triton==2.1.0 \
causal_conv1d-1.2.2.post1-cp310-cp310-linux_x86_64.whl \
mamba_ssm-2.0.3-cp310-cp310-linux_x86_64.whl \
grouped_gemm-1.1.2-cp310-cp310-linux_x86_64.whl \
tensorstore==0.1.45 && \
rm *.whl

# Since megatron does not have any dependencies (and isn't a dependency to any other package), we can install it separately to make everything a bit quicker
COPY . /opt/megatron-lm
RUN pip install /opt/megatron-lm

##### For NVIDIANS only #####
FROM main as jet
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