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‎LICENSE‎

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MIT License
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Copyright (c) 2020 Vijay Prakash Dwivedi, Chaitanya K. Joshi, Thomas Laurent, Yoshua Bengio, Xavier Bresson
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎environment_cpu.yml‎

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name: benchmark_gnn
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channels:
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- pytorch
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- dglteam
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- conda-forge
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- anaconda
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- defaults
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dependencies:
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- python=3.7.4
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- python-dateutil=2.8.0
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- pip=19.2.3
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- pytorch=1.6.0
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- torchvision==0.7.0
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- pillow==6.1
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- dgl=0.5.2
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- numpy=1.16.4
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- matplotlib=3.1.0
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- tensorboard=1.14.0
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- tensorboardx=1.8
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- future=0.18.2
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- absl-py
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- networkx=2.3
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- scikit-learn=0.21.2
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- scipy=1.3.0
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- notebook=6.0.0
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- h5py=2.9.0
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- mkl=2019.4
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- ipykernel=5.1.2
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- ipython=7.7.0
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- ipython_genutils=0.2.0
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- ipywidgets=7.5.1
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- jupyter=1.0.0
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- jupyter_client=5.3.1
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- jupyter_console=6.0.0
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- jupyter_core=4.5.0
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- plotly=4.1.1
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- scikit-image=0.15.0
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- requests==2.22.0
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- tqdm==4.43.0
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- pip:
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- tensorflow==2.1.0
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- tensorflow-estimator==2.1.0
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- tensorboard==2.1.1
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- ogb==1.2.2

‎environment_gpu.yml‎

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name: benchmark_gnn_0.5.2
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channels:
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- pytorch
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- dglteam
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- conda-forge
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- fragcolor
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- anaconda
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- defaults
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dependencies:
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- cudatoolkit=10.2
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- cudnn=7.6.5
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- python=3.7.4
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- python-dateutil=2.8.0
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- pip=19.2.3
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- pytorch=1.6.0
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- torchvision==0.7.0
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- pillow==6.1
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- dgl-cuda10.2=0.5.2
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- numpy=1.16.4
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- matplotlib=3.1.0
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- tensorboard=1.14.0
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- tensorboardx=1.8
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- future=0.18.2
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- absl-py
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- networkx=2.3
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- scikit-learn=0.21.2
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- scipy=1.3.0
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- notebook=6.0.0
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- h5py=2.9.0
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- mkl=2019.4
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- ipykernel=5.1.2
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- ipython=7.7.0
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- ipython_genutils=0.2.0
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- ipywidgets=7.5.1
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- jupyter=1.0.0
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- jupyter_client=5.3.1
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- jupyter_console=6.0.0
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- jupyter_core=4.5.0
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- plotly=4.1.1
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- scikit-image=0.15.0
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- requests==2.22.0
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- tqdm==4.43.0
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- pip:
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- tensorflow-gpu==2.1.0
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- tensorflow-estimator==2.1.0
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- tensorboard==2.1.1
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- ogb==1.2.2

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