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‎CMakeLists.txt‎

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@@ -87,12 +87,15 @@ add_definitions(-DENABLE_PARTIAL_FRONTIER=0) # disable minigun partial frontier
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# Source file lists
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file(GLOB DGL_SRC
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src/*.cc
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src/array/*.cc
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src/array/cpu/*.cc
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src/kernel/*.cc
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src/kernel/cpu/*.cc
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src/runtime/*.cc
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)
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file(GLOB_RECURSE DGL_SRC_1
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src/api/*.cc
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src/graph/*.cc
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src/scheduler/*.cc
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)

‎CONTRIBUTORS.md‎

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* [Tianyi Zhang](https://github.com/Tiiiger): SGC in Pytorch
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* [Jun Chen](https://github.com/kitaev-chen): GIN in Pytorch
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* [Aymen Waheb](https://github.com/aymenwah): APPNP in Pytorch
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* [Chengqiang Lu](https://github.com/geekinglcq): MGCN, SchNet and MPNN in PyTorch
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Other improvement
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* [Brett Koonce](https://github.com/brettkoonce)
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* [@giuseppefutia](https://github.com/giuseppefutia)
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* [@mori97](https://github.com/mori97)
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* Hao Jin
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‎Jenkinsfile‎

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@@ -94,14 +94,19 @@ def tutorial_test_linux(backend) {
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}
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pipeline {
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agent none
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agent any
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stages {
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stage("Lint Check") {
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agent { docker { image "dgllib/dgl-ci-lint" } }
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steps {
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init_git()
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sh "bash tests/scripts/task_lint.sh"
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("Build") {
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parallel {
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steps {
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build_dgl_linux("cpu")
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("GPU Build") {
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agent {
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sh "nvidia-smi"
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build_dgl_linux("gpu")
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("CPU Build (Win64)") {
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// Windows build machines are manually added to Jenkins master with
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steps {
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build_dgl_win64("cpu")
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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// Currently we don't have Windows GPU build machines
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}
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steps {
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cpp_unit_test_linux()
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("C++ CPU (Win64)") {
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agent { label "windows" }
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steps {
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cpp_unit_test_win64()
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("Torch CPU") {
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agent { docker { image "dgllib/dgl-ci-cpu" } }
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}
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}
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("Torch CPU (Win64)") {
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agent { label "windows" }
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}
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}
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("Torch GPU") {
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agent {
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}
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}
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("MXNet CPU") {
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agent { docker { image "dgllib/dgl-ci-cpu" } }
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unit_test_linux("mxnet", "cpu")
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}
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}
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//stage("Example test") {
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// steps {
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// unit_test_linux("pytorch", "cpu")
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// }
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//}
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//stage("Tutorial test") {
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// steps {
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// tutorial_test_linux("mxnet")
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// }
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//}
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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stage("MXNet GPU") {
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agent {
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unit_test_linux("mxnet", "gpu")
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}
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}
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//stage("Example test") {
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// steps {
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// unit_test_linux("pytorch", "cpu")
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// }
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//}
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//stage("Tutorial test") {
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// steps {
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// tutorial_test_linux("mxnet")
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// }
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//}
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}
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post {
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always {
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cleanWs disableDeferredWipeout: true, deleteDirs: true
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}
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}
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}
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}
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}
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}
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post {
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always {
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node('windows') {
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bat "rmvirtualenv ${BUILD_TAG}"
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}
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}
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}
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}

‎README.md‎

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# Deep Graph Library (DGL)
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[![Build Status](http://ci.dgl.ai:80/buildStatus/icon?job=DGL/master)](http://ci.dgl.ai:80/job/DGL/job/master/)
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[![GitHub license](https://dmlc.github.io/img/apache2.svg)](./LICENSE)
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[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)
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[Documentation](https://docs.dgl.ai) | [DGL at a glance](https://docs.dgl.ai/tutorials/basics/1_first.html#sphx-glr-tutorials-basics-1-first-py) |
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[Model Tutorials](https://docs.dgl.ai/tutorials/models/index.html) | [Discussion Forum](https://discuss.dgl.ai)
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| Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement |
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| ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- |
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| [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0038s | 1.34x |
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| [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0076s | 12.9x |
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| [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0031s | 1.64x |
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| [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0113s | 8.69x |
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| [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a |
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| [TreeLSTM](http://arxiv.org/abs/1503.00075) | 51.0% | 51.72% | [14.02s (DyNet)](https://github.com/clab/dynet/tree/master/examples/treelstm) | 3.18s | 4.3x |
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| [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0097s | 29.4x |
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| [R-GCN <br> (classification)](https://arxiv.org/abs/1703.06103) | 73.23% | 73.53% | [0.2853s (Theano)](https://github.com/tkipf/relational-gcn) | 0.0075s | 38.2x |
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| [R-GCN <br> (link prediction)](https://arxiv.org/abs/1703.06103) | 0.158 | 0.151 | [2.204s (TF)](https://github.com/MichSchli/RelationPrediction) | 0.453s | 4.86x |
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| [JTNN](https://arxiv.org/abs/1802.04364) | 96.44% | 96.44% | [1826s (Pytorch)](https://github.com/wengong-jin/icml18-jtnn) | 743s | 2.5x |
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| [LGNN](https://arxiv.org/abs/1705.08415) | 94% | 94% | n/a | 1.45s | n/a |
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## News
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v0.3 has just been released! Huge performance improvement (up to 19x). See release note
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[here](https://github.com/dmlc/dgl/releases/tag/v0.3).
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We presented DGL at [GTC 2019](https://www.nvidia.com/en-us/gtc/) as an
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instructor-led training session. Check out our slides and tutorial materials
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[here](https://github.com/dglai/DGL-GTC2019)!!!
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v0.2 has just been released! Many features, bugfix and performance improvement. See release note
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[here](https://github.com/dmlc/dgl/releases/tag/v0.2).
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## System requirements
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‎cmake/modules/CUDA.cmake‎

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src/array/cuda/*.cc
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src/array/cuda/*.cu
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‎conda/dgl/meta.yaml‎

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package:
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name: dgl{{ environ.get('DGL_PACKAGE_SUFFIX', '') }}
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version: "0.3"
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version: "0.4"
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source:
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git_rev: 0.3.x

‎docs/README.md‎

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------------
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* sphinx
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* sphinx-gallery
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* sphinx_rtd_theme
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* Both pytorch and mxnet installed.
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Build documents

‎docs/source/api/python/batch.rst‎

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mean_edges
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max_nodes
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max_edges
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topk_nodes
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topk_edges
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softmax_nodes
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softmax_edges
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broadcast_nodes
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broadcast_edges

‎docs/source/api/python/function.rst‎

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copy_src
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copy_edge
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src_mul_edge
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copy_u
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copy_e
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u_add_v
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u_sub_v
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u_mul_v
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u_div_v
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u_add_e
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u_sub_e
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u_mul_e
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u_div_e
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v_add_u
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v_sub_u
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v_mul_u
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v_div_u
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v_add_e
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v_sub_e
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v_mul_e
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v_div_e
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e_add_u
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e_sub_u
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e_mul_u
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e_div_u
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e_add_v
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e_sub_v
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e_mul_v
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e_div_v
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Reduce functions
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sum
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min
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prod
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mean

‎docs/source/api/python/graph.rst‎

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DGLGraph.set_n_initializer
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DGLGraph.set_e_initializer
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DGLGraph.local_var
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DGLGraph.local_scope
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Computing with DGLGraph
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-----------------------

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