-
def prepare_data(data_platform: str = "10XVisium", sample_number: int = 151507, split_number: int = 0, \
preprocessed: bool = True, impute_gene_type: str = "all", \
…
-
### 🐛 Describe the bug
I am having this issue with my model as
```
from torch_geometric.nn import SAGEConv, to_hetero,GraphConv
from torch.nn import Linear
from torch_geometric.utils import to_u…
-
From now on, we recommend using our discussion forum (https://github.com/rusty1s/pytorch_geometric/discussions) for general questions.
## ❓ Questions & Help
I am new to PyG framework, and having…
-
Hi. Thanks for sharing your code. I wanted to implement the HGT model on my heterogeneous graph but I don't have any temporal element in my data. From what I could understand, I would have to modify t…
-
As written, [Heterogeneous Paxos](https://arxiv.org/abs/2011.08253) assumes a learner graph that does not change over time.
Technically, of course, we can encode all learners from all points in time …
-
Dear author, is this model from the paper "Heterogeneous graph traffic prediction considering spatial information around roads"?
-
**Describe the bug**
Traceback (most recent call last):
File "/home/xxx/autoGL/ai1.py", line 6, in
custom_static_homogeneous_graph = GeneralStaticGraphGenerator.create_homogeneous_static_gra…
-
Hello, I'm looking for a way to use RGCNConv with heterogeneous graphs (different node types and edges). I understand that RGCNConv can handle different edge types by passing in **edge_type** along wi…
-
## Description
RelationService aggregates all identities by recording all Web2 and Web3 platform connections.
Based on GraphDB, we provide graph solutions for on-chain and off-chain identity relatio…
-
## 🚀 Feature
*mod_args.get(etype,()) and **mod_kwargs.get(etype,{}) in HeteroGraphConv's forward need to be changed to *mod_args.get((stype, etype, dtype),()) and **mod_kwargs.get((stype, etype, dt…