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# MLCube for Graph Neural Network | ||
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MLCube™ GitHub [repository](https://github.com/mlcommons/mlcube). MLCube™ [wiki](https://mlcommons.github.io/mlcube/). | ||
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## Project setup | ||
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An important requirement is that you must have Docker installed. | ||
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```bash | ||
# Create Python environment and install MLCube Docker runner | ||
virtualenv -p python3 ./env && source ./env/bin/activate && pip install pip==24.0 && pip install mlcube-docker | ||
# Fetch the implementation from GitHub | ||
git clone https://github.com/mlcommons/training && cd ./training | ||
git fetch origin pull/762/head:feature/mlcube_graph_nn && git checkout feature/mlcube_graph_nn | ||
cd ./graph_neural_network/mlcube | ||
``` | ||
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Inside the mlcube directory run the following command to check implemented tasks. | ||
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```shell | ||
mlcube describe | ||
``` | ||
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### MLCube tasks | ||
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* Core tasks: | ||
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Download dataset. | ||
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```shell | ||
mlcube run --task=download_data -Pdocker.build_strategy=always | ||
``` | ||
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Process dataset. | ||
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```shell | ||
mlcube run --task=process_data -Pdocker.build_strategy=always | ||
``` | ||
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Train GNN. | ||
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```shell | ||
mlcube run --task=train -Pdocker.build_strategy=always | ||
``` | ||
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* Demo tasks: | ||
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Download demo dataset. | ||
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```shell | ||
mlcube run --task=download_demo -Pdocker.build_strategy=always | ||
``` | ||
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Run demo training. | ||
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```shell | ||
mlcube run --task=demo -Pdocker.build_strategy=always | ||
``` | ||
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### Execute the complete pipeline | ||
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You can execute the complete pipeline with one single command. | ||
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* Core pipeline: | ||
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```shell | ||
mlcube run --task=download_data,process_data,train -Pdocker.build_strategy=always | ||
``` | ||
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* Demo pipeline: | ||
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```shell | ||
mlcube run --task=download_demo,demo -Pdocker.build_strategy=always | ||
``` |