Merge branch 'master' into zecheng_isolate_bipartite

.pre-commit-config.yaml

@@ -34,7 +34,7 @@ repos:
         args: [-d, '{extends: default, rules: {line-length: disable, document-start: disable, truthy: {level: error}, braces: {max-spaces-inside: 1}}}']
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.17.0
+    rev: v3.19.1
     hooks:
       - id: pyupgrade
         name: Upgrade Python syntax
@@ -54,7 +54,7 @@ repos:
         ]
 
   - repo: https://github.com/google/yapf
-    rev: v0.40.2
+    rev: v0.43.0
     hooks:
       - id: yapf
         name: Format code
@@ -74,14 +74,14 @@ repos:
         additional_dependencies: [Flake8-pyproject]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.9
+    rev: v0.8.6
     hooks:
       - id: ruff
         name: Ruff formatting
         args: [--fix, --exit-non-zero-on-fix]
 
   - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.17
+    rev: 0.7.21
     hooks:
       - id: mdformat
         name: Format Markdown

CHANGELOG.md

@@ -3,7 +3,7 @@
 All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
-## \[2.7.0\] - 2024-MM-DD
+## [2.7.0] - 2024-MM-DD
 
 ### Added
 
@@ -39,7 +39,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
-## \[2.6.0\] - 2024-09-13
+## [2.6.0] - 2024-09-13
 
 ### Added
 
@@ -132,7 +132,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
-## \[2.5.0\] - 2024-02-16
+## [2.5.0] - 2024-02-16
 
 ### Added
 
@@ -232,7 +232,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed disabling of extension packages during `torch_geometric.compile` ([#8698](https://github.com/pyg-team/pytorch_geometric/pull/8698))
 
-## \[2.4.0\] - 2023-10-12
+## [2.4.0] - 2023-10-12
 
 ### Added
 
@@ -288,7 +288,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added back support for PyTorch >= 1.11.0 ([#7656](https://github.com/pyg-team/pytorch_geometric/pull/7656))
 - Added `Data.sort()` and `HeteroData.sort()` functionalities ([#7649](https://github.com/pyg-team/pytorch_geometric/pull/7649))
 - Added `torch.nested_tensor` support in `Data` and `Batch` ([#7643](https://github.com/pyg-team/pytorch_geometric/pull/7643), [#7647](https://github.com/pyg-team/pytorch_geometric/pull/7647))
-- Added `interval` argument to `Cartesian`, `LocalCartesian` and `Distance` transformations ([#7533](https://github.com/pyg-team/pytorch_geometric/pull/7533), [#7614](https://github.com/pyg-team/pytorch_geometric/pull/7614),  [#7700](https://github.com/pyg-team/pytorch_geometric/pull/7700))
+- Added `interval` argument to `Cartesian`, `LocalCartesian` and `Distance` transformations ([#7533](https://github.com/pyg-team/pytorch_geometric/pull/7533), [#7614](https://github.com/pyg-team/pytorch_geometric/pull/7614), [#7700](https://github.com/pyg-team/pytorch_geometric/pull/7700))
 - Added a `LightGCN` example on the `AmazonBook` dataset ([7603](https://github.com/pyg-team/pytorch_geometric/pull/7603))
 - Added a tutorial on hierarchical neighborhood sampling ([#7594](https://github.com/pyg-team/pytorch_geometric/pull/7594))
 - Enabled different attention modes in `HypergraphConv` via the `attention_mode` argument ([#7601](https://github.com/pyg-team/pytorch_geometric/pull/7601))
@@ -357,7 +357,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed the `trim_to_layer` function to filter out non-reachable node and edge types when operating on heterogeneous graphs ([#7942](https://github.com/pyg-team/pytorch_geometric/pull/7942))
 - Accelerated and simplified `top_k` computation in `TopKPooling` ([#7737](https://github.com/pyg-team/pytorch_geometric/pull/7737))
 - Updated `GIN` implementation in kernel benchmarks to have sequential batchnorms ([#7955](https://github.com/pyg-team/pytorch_geometric/pull/7955))
-- Fixed bugs in benchmarks caused by a lack of the device conditions for CPU and unexpected `cache` argument in heterogeneous  models ([#7956](https://github.com/pyg-team/pytorch_geometric/pull/7956)
+- Fixed bugs in benchmarks caused by a lack of the device conditions for CPU and unexpected `cache` argument in heterogeneous models ([#7956](https://github.com/pyg-team/pytorch_geometric/pull/7956)
 - Fixed a bug in which `batch.e_id` was not correctly computed on unsorted graph inputs ([#7953](https://github.com/pyg-team/pytorch_geometric/pull/7953))
 - Fixed `from_networkx` conversion from `nx.stochastic_block_model` graphs ([#7941](https://github.com/pyg-team/pytorch_geometric/pull/7941))
 - Fixed the usage of `bias_initializer` in `HeteroLinear` ([#7923](https://github.com/pyg-team/pytorch_geometric/pull/7923))
@@ -424,7 +424,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed `layer_type` argument in `contrib.explain.GraphMaskExplainer` ([#7445](https://github.com/pyg-team/pytorch_geometric/pull/7445))
 - Replaced `FastHGTConv` with `HGTConv` ([#7117](https://github.com/pyg-team/pytorch_geometric/pull/7117))
 
-## \[2.3.0\] - 2023-03-23
+## [2.3.0] - 2023-03-23
 
 ### Added
 
@@ -582,7 +582,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed `target_index` argument in the `Explainer` interface ([#6270](https://github.com/pyg-team/pytorch_geometric/pull/6270))
 - Removed `Aggregation.set_validate_args` option ([#6175](https://github.com/pyg-team/pytorch_geometric/pull/6175))
 
-## \[2.2.0\] - 2022-12-01
+## [2.2.0] - 2022-12-01
 
 ### Added
 
@@ -700,7 +700,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed `scatter_reduce` option from experimental mode ([#5399](https://github.com/pyg-team/pytorch_geometric/pull/5399))
 
-## \[2.1.0\] - 2022-08-17
+## [2.1.0] - 2022-08-17
 
 ### Added
 

README.md

@@ -109,7 +109,7 @@ More information about evaluating final model performance can be found in the co
 In addition to the easy application of existing GNNs, PyG makes it simple to implement custom Graph Neural Networks (see [here](https://pytorch-geometric.readthedocs.io/en/latest/tutorial/create_gnn.html) for the accompanying tutorial).
 For example, this is all it takes to implement the [edge convolutional layer](https://arxiv.org/abs/1801.07829) from Wang *et al.*:
 
-$$x_i^{\\prime} ~ = ~ \\max\_{j \\in \\mathcal{N}(i)} ~ \\textrm{MLP}\_{\\theta} \\left( \[ ~ x_i, ~ x_j - x_i ~ \] \\right)$$
+$$x_i^{\\prime} ~ = ~ \\max\_{j \\in \\mathcal{N}(i)} ~ \\textrm{MLP}\_{\\theta} \\left( [ ~ x_i, ~ x_j - x_i ~ ] \\right)$$
 
 ```python
 import torch

docs/source/get_started/introduction.rst

@@ -176,7 +176,7 @@ We can even use slices, long or bool tensors to split the dataset.
     test_dataset = dataset[540:]
     >>> ENZYMES(60)
 
-If you are unsure whether the dataset is already shuffled before you split, you can randomly permutate it by running:
+If you are unsure whether the dataset is already shuffled before you split, you can randomly permute it by running:
 
 .. code-block:: python
 

examples/distributed/pyg/README.md

@@ -22,7 +22,7 @@ To run the example, please refer to the steps below.
 - Password-less SSH needs to be set up on all the nodes that you are using (see the [Linux SSH manual](https://linuxize.com/post/how-to-setup-passwordless-ssh-login)).
 - All nodes need to have a consistent environments installed, specifically `torch` and `pyg-lib` versions must be the same.
   You might want to consider using docker containers.
-- *\[Optional\]* In some cases Linux firewall might be blocking TCP connection issues.
+- *[Optional]* In some cases Linux firewall might be blocking TCP connection issues.
   Ensure that firewall settings allow for all nodes to communicate (see the [Linux firewall manual](https://ubuntu.com/server/docs/security-firewall)).
   For this example TCP ports `11111`, `11112` and `11113` should be open (*i.e.* `sudo ufw allow 11111`).