Unverified Commit a5a052b5 authored by VoVAllen's avatar VoVAllen Committed by GitHub
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[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 ...@@ -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: 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 | | 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 | | [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 | | [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 | | [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 ...@@ -75,13 +75,14 @@ conda install -c dglteam dgl-cuda10.1 # CUDA 10.1
### Using pip ### Using pip
```
pip install dgl # cpu version | | Latest Nightly Build Version | Stable Version |
pip install dgl-cu90 # CUDA 9.0 |-----------|-------------------------------|-------------------------|
pip install dgl-cu92 # CUDA 9.2 | CPU | `pip install --pre dgl` | `pip install dgl` |
pip install dgl-cu100 # CUDA 10.0 | CUDA 9.0 | `pip install --pre dgl-cu90` | `pip install dgl-cu90` |
pip install dgl-cu101 # CUDA 10.1 | 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 ### From source
......
...@@ -30,7 +30,7 @@ class GNNBenchmarkDataset(object): ...@@ -30,7 +30,7 @@ class GNNBenchmarkDataset(object):
@staticmethod @staticmethod
def load_npz(file_name): 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) loader = dict(loader)
num_nodes = loader['adj_shape'][0] num_nodes = loader['adj_shape'][0]
adj_matrix = sp.csr_matrix((loader['adj_data'], loader['adj_indices'], loader['adj_indptr']), adj_matrix = sp.csr_matrix((loader['adj_data'], loader['adj_indices'], loader['adj_indptr']),
...@@ -116,7 +116,7 @@ class AmazonCoBuy(GNNBenchmarkDataset): ...@@ -116,7 +116,7 @@ class AmazonCoBuy(GNNBenchmarkDataset):
Parameters Parameters
--------------- ---------------
name: str name: str
Name of the dataset, has to be 'computer' or 'photo' Name of the dataset, has to be 'computers' or 'photo'
""" """
_url = { _url = {
......
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