Commit 6c3dba86 authored by Giuseppe Futia's avatar Giuseppe Futia Committed by Lingfan Yu
Browse files

[Tutorial] Update prerequisites of README (#380)

* Update prerequisites of README

* dependencies for pytorch models

* dependencies for mxnet models

* minor
parent 29dd22e6
...@@ -7,8 +7,17 @@ Graph Attention Networks (GAT) ...@@ -7,8 +7,17 @@ Graph Attention Networks (GAT)
Note that the original code is implemented with Tensorflow for the paper. Note that the original code is implemented with Tensorflow for the paper.
### Dependencies
* MXNet nightly build
* requests
## Usage (make sure that DGLBACKEND is changed into mxnet) ```bash
pip install mxnet --pre
pip install requests
```
### Usage (make sure that DGLBACKEND is changed into mxnet)
```bash ```bash
DGLBACKEND=mxnet python gat_batch.py --dataset cora --gpu 0 --num-heads 8 DGLBACKEND=mxnet python gat_batch.py --dataset cora --gpu 0 --num-heads 8
``` ```
...@@ -4,11 +4,13 @@ Graph Convolutional Networks (GCN) ...@@ -4,11 +4,13 @@ Graph Convolutional Networks (GCN)
Paper link: [https://arxiv.org/abs/1609.02907](https://arxiv.org/abs/1609.02907) Paper link: [https://arxiv.org/abs/1609.02907](https://arxiv.org/abs/1609.02907)
Author's code repo: [https://github.com/tkipf/gcn](https://github.com/tkipf/gcn) Author's code repo: [https://github.com/tkipf/gcn](https://github.com/tkipf/gcn)
Requirements Dependencies
------------ ------------
- MXNet nightly build
- requests - requests
``bash ``bash
pip install mxnet --pre
pip install requests pip install requests
`` ``
......
...@@ -4,12 +4,19 @@ ...@@ -4,12 +4,19 @@
* Author's code for entity classification: [https://github.com/tkipf/relational-gcn](https://github.com/tkipf/relational-gcn) * Author's code for entity classification: [https://github.com/tkipf/relational-gcn](https://github.com/tkipf/relational-gcn)
* Author's code for link prediction: [https://github.com/MichSchli/RelationPrediction](https://github.com/MichSchli/RelationPrediction) * Author's code for link prediction: [https://github.com/MichSchli/RelationPrediction](https://github.com/MichSchli/RelationPrediction)
### Prerequisites ### Dependencies
Two extra python packages are needed for this example: Two extra python packages are needed for this example:
- MXNet nightly build
- requests
- rdflib - rdflib
- pandas - pandas
```bash
pip install mxnet --pre
pip install requests rdflib pandas
```
Example code was tested with rdflib 4.2.2 and pandas 0.23.4 Example code was tested with rdflib 4.2.2 and pandas 0.23.4
### Entity Classification ### Entity Classification
......
...@@ -4,6 +4,16 @@ Benchmark SSE on multi-GPUs ...@@ -4,6 +4,16 @@ Benchmark SSE on multi-GPUs
Paper link: Paper link:
[http://proceedings.mlr.press/v80/dai18a/dai18a.pdf](http://proceedings.mlr.press/v80/dai18a/dai18a.pdf) [http://proceedings.mlr.press/v80/dai18a/dai18a.pdf](http://proceedings.mlr.press/v80/dai18a/dai18a.pdf)
Dependencies
-------------
* MXNet nightly build
* requests
```bash
pip install mxnet --pre
pip install requests
```
Use a small embedding Use a small embedding
--------------------- ---------------------
......
...@@ -6,6 +6,16 @@ This is a re-implementation of the following paper: ...@@ -6,6 +6,16 @@ This is a re-implementation of the following paper:
The provided implementation can achieve a test accuracy of 51.72 which is comparable with the result reported in the original paper: 51.0(±0.5). The provided implementation can achieve a test accuracy of 51.72 which is comparable with the result reported in the original paper: 51.0(±0.5).
## Dependencies
* MXNet nightly build
* requests
* nltk
```bash
pip install mxnet --pre
pip install requests nltk
```
## Data ## Data
The script will download the [SST dataset] (http://nlp.stanford.edu/sentiment/index.html) and the GloVe 840B.300d embedding automatically if `--use-glove` is specified (note: download may take a while). The script will download the [SST dataset] (http://nlp.stanford.edu/sentiment/index.html) and the GloVe 840B.300d embedding automatically if `--use-glove` is specified (note: download may take a while).
......
...@@ -4,7 +4,17 @@ DGL implementation of Capsule Network ...@@ -4,7 +4,17 @@ DGL implementation of Capsule Network
This repo implements Hinton and his team's [Capsule Network](https://arxiv.org/abs/1710.09829). This repo implements Hinton and his team's [Capsule Network](https://arxiv.org/abs/1710.09829).
Only margin loss is implemented, for simplicity to understand the DGL. Only margin loss is implemented, for simplicity to understand the DGL.
## Training& Evaluation Dependencies
--------------
* PyTorch 0.4.1+
* torchvision
```bash
pip install torch torchvision
```
Training & Evaluation
----------------------
```bash ```bash
# Run with default config # Run with default config
python main.py python main.py
......
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
This is an implementation of [Learning Deep Generative Models of Graphs](https://arxiv.org/pdf/1803.03324.pdf) by This is an implementation of [Learning Deep Generative Models of Graphs](https://arxiv.org/pdf/1803.03324.pdf) by
Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, Peter Battaglia. Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, Peter Battaglia.
## Dependency ## Dependencies
- Python 3.5.2 - Python 3.5.2
- [Pytorch 0.4.1](https://pytorch.org/) - [Pytorch 0.4.1](https://pytorch.org/)
- [Matplotlib 2.2.2](https://matplotlib.org/) - [Matplotlib 2.2.2](https://matplotlib.org/)
......
...@@ -7,7 +7,7 @@ Graph Attention Networks (GAT) ...@@ -7,7 +7,7 @@ Graph Attention Networks (GAT)
- Popular pytorch implementation: - Popular pytorch implementation:
[https://github.com/Diego999/pyGAT](https://github.com/Diego999/pyGAT). [https://github.com/Diego999/pyGAT](https://github.com/Diego999/pyGAT).
Requirements Dependencies
------------ ------------
- torch v1.0: the autograd support for sparse mm is only available in v1.0. - torch v1.0: the autograd support for sparse mm is only available in v1.0.
- requests - requests
......
...@@ -5,12 +5,13 @@ Graph Convolutional Networks (GCN) ...@@ -5,12 +5,13 @@ Graph Convolutional Networks (GCN)
- Author's code repo: [https://github.com/tkipf/gcn](https://github.com/tkipf/gcn). Note that the original code is - Author's code repo: [https://github.com/tkipf/gcn](https://github.com/tkipf/gcn). Note that the original code is
implemented with Tensorflow for the paper. implemented with Tensorflow for the paper.
Requirements Dependencies
------------ ------------
- PyTorch 0.4.1+
- requests - requests
``bash ``bash
pip install requests pip install torch requests
`` ``
Codes Codes
......
Junction Tree VAE - example for training Junction Tree VAE - example for training
=== ==========================================
This is a direct modification from https://github.com/wengong-jin/icml18-jtnn This is a direct modification from https://github.com/wengong-jin/icml18-jtnn
You need to have RDKit installed. Dependencies
--------------
* PyTorch 0.4.1+
* RDKit
* requests
How to run
-----------
To run the model, use To run the model, use
``` ```
......
...@@ -7,6 +7,18 @@ Author's code repo: [https://github.com/joanbruna/GNN_community](https://github. ...@@ -7,6 +7,18 @@ Author's code repo: [https://github.com/joanbruna/GNN_community](https://github.
This folder contains a DGL implementation of the CDGNN model. This folder contains a DGL implementation of the CDGNN model.
Dependencies
--------------
* PyTorch 0.4.1+
* requests
```bash
pip install torch requests
```
How to run
----------
An experiment on the Stochastic Block Model in default settings can be run with An experiment on the Stochastic Block Model in default settings can be run with
```bash ```bash
......
...@@ -4,11 +4,15 @@ ...@@ -4,11 +4,15 @@
* Author's code for entity classification: [https://github.com/tkipf/relational-gcn](https://github.com/tkipf/relational-gcn) * Author's code for entity classification: [https://github.com/tkipf/relational-gcn](https://github.com/tkipf/relational-gcn)
* Author's code for link prediction: [https://github.com/MichSchli/RelationPrediction](https://github.com/MichSchli/RelationPrediction) * Author's code for link prediction: [https://github.com/MichSchli/RelationPrediction](https://github.com/MichSchli/RelationPrediction)
### Prerequisites ### Dependencies
Two extra python packages are needed for this example: * PyTorch 0.4.1+
* requests
* rdflib
* pandas
- rdflib ```
- pandas pip install requests torch rdflib pandas
```
Example code was tested with rdflib 4.2.2 and pandas 0.23.4 Example code was tested with rdflib 4.2.2 and pandas 0.23.4
......
...@@ -3,11 +3,12 @@ In this example we implement the [Transformer](https://arxiv.org/pdf/1706.03762. ...@@ -3,11 +3,12 @@ In this example we implement the [Transformer](https://arxiv.org/pdf/1706.03762.
The folder contains training module and inferencing module (beam decoder) for Transformer and training module for Universal Transformer The folder contains training module and inferencing module (beam decoder) for Transformer and training module for Universal Transformer
## Requirements ## Dependencies
- PyTorch 0.4.1+ - PyTorch 0.4.1+
- networkx - networkx
- tqdm - tqdm
- requests
## Usage ## Usage
......
...@@ -13,6 +13,15 @@ wget http://nlp.stanford.edu/data/glove.840B.300d.zip ...@@ -13,6 +13,15 @@ wget http://nlp.stanford.edu/data/glove.840B.300d.zip
unzip glove.840B.300d.zip unzip glove.840B.300d.zip
``` ```
## Dependencies
* PyTorch 0.4.1+
* requests
* nltk
```
pip install torch requests nltk
```
## Usage ## Usage
``` ```
python train.py --gpu 0 python train.py --gpu 0
......
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