Unverified Commit a5a052b5 authored by VoVAllen's avatar VoVAllen Committed by GitHub
Browse files

[Fix] Fix #1078, #1077 and add nightly build to readme

parent fa0ee46a
......@@ -18,7 +18,7 @@ All model examples can be found [here](https://github.com/dmlc/dgl/tree/master/e
A summary of part of the model accuracy and training speed with the Pytorch backend (on Amazon EC2 p3.2x instance (w/ V100 GPU)), as compared with the best open-source implementations:
| Model | Reported <br> Accuracy | DGL <br> Accuracy | Author's training speed (epoch time) | DGL speed (epoch time) | Improvement |
| ----- | ----------------- | ------------ | ------------------------------------ | ---------------------- | ----------- |
| ---------------------------------------------------------------- | ---------------------- | ----------------- | ----------------------------------------------------------------------------- | ---------------------- | ----------- |
| [GCN](https://arxiv.org/abs/1609.02907) | 81.5% | 81.0% | [0.0051s (TF)](https://github.com/tkipf/gcn) | 0.0031s | 1.64x |
| [GAT](https://arxiv.org/abs/1710.10903) | 83.0% | 83.9% | [0.0982s (TF)](https://github.com/PetarV-/GAT) | 0.0113s | 8.69x |
| [SGC](https://arxiv.org/abs/1902.07153) | 81.0% | 81.9% | n/a | 0.0008s | n/a |
......@@ -75,13 +75,14 @@ conda install -c dglteam dgl-cuda10.1 # CUDA 10.1
### Using pip
```
pip install dgl # cpu version
pip install dgl-cu90 # CUDA 9.0
pip install dgl-cu92 # CUDA 9.2
pip install dgl-cu100 # CUDA 10.0
pip install dgl-cu101 # CUDA 10.1
```
| | Latest Nightly Build Version | Stable Version |
|-----------|-------------------------------|-------------------------|
| CPU | `pip install --pre dgl` | `pip install dgl` |
| CUDA 9.0 | `pip install --pre dgl-cu90` | `pip install dgl-cu90` |
| CUDA 9.2 | `pip install --pre dgl-cu92` | `pip install dgl-cu92` |
| CUDA 10.0 | `pip install --pre dgl-cu100` | `pip install dgl-cu100` |
| CUDA 10.1 | `pip install --pre dgl-cu101` | `pip install dgl-cu101` |
### From source
......
......@@ -30,7 +30,7 @@ class GNNBenchmarkDataset(object):
@staticmethod
def load_npz(file_name):
with np.load(file_name) as loader:
with np.load(file_name, allow_pickle=True) as loader:
loader = dict(loader)
num_nodes = loader['adj_shape'][0]
adj_matrix = sp.csr_matrix((loader['adj_data'], loader['adj_indices'], loader['adj_indptr']),
......@@ -116,7 +116,7 @@ class AmazonCoBuy(GNNBenchmarkDataset):
Parameters
---------------
name: str
Name of the dataset, has to be 'computer' or 'photo'
Name of the dataset, has to be 'computers' or 'photo'
"""
_url = {
......
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