wehub-resource-sync
79 lines
2.6 KiB
Bash
79 lines
2.6 KiB
Bash
#!/bin/bash
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# The script launches a docker container to run ASV benchmarks. We use the same docker
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# image as our CI (i.e., dgllib/dgl-ci-gpu:conda). It performs the following steps:
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#
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# 1. Start a docker container of the given machine name. The machine name will be
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# displayed on the generated website.
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# 2. Copy `.git` into the container. It allows ASV to determine the repository information
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# such as commit hash, branches, etc.
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# 3. Copy this folder into the container including the ASV configuration file `asv.conf.json`.
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# This means any changes to the files in this folder do not
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# require a git commit. By contrast, to correctly benchmark your changes to the core
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# library (e.g., "python/dgl"), you must call git commit first.
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# 4. It then calls the `run.sh` script inside the container. It will invoke `asv run`.
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# You can change the command such as specifying the benchmarks to run or adding some flags.
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# 5. After benchmarking, it copies the generated `results` and `html` folders back to
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# the host machine.
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#
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if [ $# -eq 2 ]; then
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MACHINE=$1
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DEVICE=$2
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else
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echo "publish.sh <machine_name> <device>"
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exit 1
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fi
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WS_ROOT=/asv/dgl
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docker pull public.ecr.aws/s1o7b3d9/benchmark_test:cu116_v230110
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if [ -z "$DGL_REG_CONF" ]; then
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DOCKER_ENV_OPT="$DOCKER_ENV_OPT"
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else
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DOCKER_ENV_OPT=" -e DGL_REG_CONF=$DGL_REG_CONF $DOCKER_ENV_OPT"
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fi
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if [ -z "$INSTANCE_TYPE" ]; then
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DOCKER_ENV_OPT="$DOCKER_ENV_OPT"
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else
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DOCKER_ENV_OPT=" -e INSTANCE_TYPE=$INSTANCE_TYPE $DOCKER_ENV_OPT"
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fi
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if [ -z "$MOUNT_PATH" ]; then
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DOCKER_MOUNT_OPT=""
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else
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DOCKER_MOUNT_OPT="-v ${MOUNT_PATH}:/tmp/dataset -v ${MOUNT_PATH}/dgl_home/:/root/.dgl/"
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fi
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echo $HOME
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echo "Mount Point: ${DOCKER_MOUNT_OPT}"
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echo "Env opt: ${DOCKER_ENV_OPT}"
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echo "DEVICE: ${DEVICE}"
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if [[ $DEVICE == "cpu" ]]; then
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docker run --name dgl-reg \
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--rm \
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$DOCKER_MOUNT_OPT \
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$DOCKER_ENV_OPT \
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--shm-size="16g" \
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--hostname=$MACHINE -dit public.ecr.aws/s1o7b3d9/benchmark_test:cu116_v230110 /bin/bash
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else
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docker run --name dgl-reg \
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--rm --gpus all \
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$DOCKER_MOUNT_OPT \
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$DOCKER_ENV_OPT \
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--shm-size="16g" \
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--hostname=$MACHINE -dit public.ecr.aws/s1o7b3d9/benchmark_test:cu116_v230110 /bin/bash
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fi
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pwd
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docker exec dgl-reg mkdir -p $WS_ROOT
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docker cp ../../.git dgl-reg:$WS_ROOT
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docker cp ../ dgl-reg:$WS_ROOT/benchmarks/
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docker cp torch_gpu_pip.txt dgl-reg:/asv
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docker exec $DOCKER_ENV_OPT dgl-reg bash $WS_ROOT/benchmarks/run.sh $DEVICE
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docker cp dgl-reg:$WS_ROOT/benchmarks/results ../
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docker cp dgl-reg:$WS_ROOT/benchmarks/html ../
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docker stop dgl-reg
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