Merge branch 'master' into feature/adding_ssma_aggregation

.github/actions/setup/action.yml

@@ -6,13 +6,13 @@ inputs:
     default: '3.9'
   torch-version:
     required: false
-    default: '2.4.0'
+    default: '2.5.0'
   cuda-version:
     required: false
     default: cpu
   torchvision-version:
     required: false
-    default: '0.19.0'
+    default: '0.20.0'
   full_install:
     required: false
     default: true
@@ -31,7 +31,6 @@ runs:
           pyproject.toml
 
     - name: Install numpy
-      if: ${{ runner.os == 'Windows' }}
       run: |
         pip install "numpy<2"
       shell: bash

.github/workflows/building_pyg_conda.yml

@@ -12,7 +12,7 @@ jobs:
       matrix:
         os: [ubuntu-20.04, macos-14, windows-2019]
         python-version: ['3.9', '3.10', '3.11', '3.12']
-        torch-version: [2.3.0, 2.4.0]
+        torch-version: [2.4.0, 2.5.0]
         cuda-version: ['cpu', 'cu118', 'cu121', 'cu124']
         exclude:
           - torch-version: 2.3.0

.github/workflows/building_rusty1s_conda.yml

@@ -12,7 +12,7 @@ jobs:
       matrix:
         os: [ubuntu-20.04, macos-14, windows-2019]
         python-version: ['3.9', '3.10', '3.11', '3.12']
-        torch-version: [2.3.0, 2.4.0]
+        torch-version: [2.4.0, 2.5.0]
         cuda-version: ['cpu', 'cu118', 'cu121', 'cu124']
         exclude:
           - torch-version: 2.3.0

.github/workflows/dist_testing.yml

@@ -6,6 +6,11 @@ on:  # yamllint disable-line rule:truthy
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   dist_pytest:

.github/workflows/documentation.yml

@@ -6,6 +6,11 @@ on:  # yamllint disable-line rule:truthy
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   make_html:

.github/workflows/full_testing.yml

@@ -16,7 +16,7 @@ jobs:
       matrix:
         os: [ubuntu-latest, windows-latest, macos-14]
         python-version: ['3.9', '3.10']
-        torch-version: [1.13.0, 2.0.0, 2.1.0, 2.2.0, 2.3.0, 2.4.0, nightly]
+        torch-version: [1.13.0, 2.0.0, 2.1.0, 2.2.0, 2.3.0, 2.4.0, 2.5.0, nightly]
         include:
           - torch-version: 1.13.0
             torchvision-version: 0.14.0
@@ -30,6 +30,8 @@ jobs:
             torchvision-version: 0.18.0
           - torch-version: 2.4.0
             torchvision-version: 0.19.0
+          - torch-version: 2.5.0
+            torchvision-version: 0.20.0
           - torch-version: nightly
             torchvision-version: nightly
         exclude:

.github/workflows/latest_testing.yml

@@ -6,6 +6,11 @@ on:  # yamllint disable-line rule:truthy
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   latest_pytest:

.github/workflows/linting.yml

@@ -6,6 +6,11 @@ on:  # yamllint disable-line rule:truthy
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   mypy:

.github/workflows/minimal_testing.yml

@@ -1,11 +1,16 @@
-name: Testing minimal PyTorch 2.4
+name: Testing minimal PyTorch 2.5
 
 on:  # yamllint disable-line rule:truthy
   push:
     branches:
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   minimal_pytest:

.github/workflows/nightly.yml

@@ -5,6 +5,11 @@ on:  # yamllint disable-line rule:truthy
   schedule:
     - cron: "0 6 * * *"  # Everyday at 6:00am UTC/10:00pm PST
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   build:

.github/workflows/prev_testing.yml

@@ -6,6 +6,11 @@ on:  # yamllint disable-line rule:truthy
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   prev_pytest:
@@ -14,14 +19,14 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        torch-version: [1.13.0, 2.1.0, 2.3.0]
+        torch-version: [1.13.0, 2.1.0, 2.4.0]
         include:
           - torch-version: 1.13.0
             torchvision-version: 0.14.0
           - torch-version: 2.1.0
             torchvision-version: 0.16.0
-          - torch-version: 2.3.0
-            torchvision-version: 0.18.0
+          - torch-version: 2.4.0
+            torchvision-version: 0.19.0
 
     steps:
       - name: Checkout repository
@@ -54,7 +59,7 @@ jobs:
       - name: Install main package
         if: steps.changed-files-specific.outputs.only_changed != 'true'
         run: |
-          pip install -e .[full,test]
+          pip install -e .[test]
 
       - name: Run tests
         if: steps.changed-files-specific.outputs.only_changed != 'true'

.github/workflows/testing.yml

@@ -1,11 +1,16 @@
-name: Testing PyTorch 2.4
+name: Testing PyTorch 2.5
 
 on:  # yamllint disable-line rule:truthy
   push:
     branches:
       - master
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}-${{ startsWith(github.ref, 'refs/pull/') || github.run_number }}  # yamllint disable-line
+  # Only cancel intermediate builds if on a PR:
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
 
   pytest:

CHANGELOG.md

@@ -7,6 +7,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
+- Added support for fast `Delaunay()` triangulation via the `torch_delaunay` package ([#9748](https://github.com/pyg-team/pytorch_geometric/pull/9748))
+- Added PyTorch 2.5 support ([#9779](https://github.com/pyg-team/pytorch_geometric/pull/9779), [#9779](https://github.com/pyg-team/pytorch_geometric/pull/9780))
+- Support 3D tetrahedral mesh elements of shape `[4, num_faces]` in the `FaceToEdge` transformation ([#9776](https://github.com/pyg-team/pytorch_geometric/pull/9776))
 - Added the `use_pcst` option to `WebQSPDataset` ([#9722](https://github.com/pyg-team/pytorch_geometric/pull/9722))
 - Allowed users to pass `edge_weight` to `GraphUNet` models ([#9737](https://github.com/pyg-team/pytorch_geometric/pull/9737))
 - Consolidated `examples/ogbn_{papers_100m,products_gat,products_sage}.py` into `examples/ogbn_train.py` ([#9467](https://github.com/pyg-team/pytorch_geometric/pull/9467))
@@ -20,6 +23,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
+- Fixed the `k_hop_subgraph()` method for directed graphs ([#9756](https://github.com/pyg-team/pytorch_geometric/pull/9756))
+- Fixed `utils.group_cat` concatenating dimension ([#9766](https://github.com/pyg-team/pytorch_geometric/pull/9766))
 - Fixed `WebQSDataset.process` raising exceptions ([#9665](https://github.com/pyg-team/pytorch_geometric/pull/9665))
 
 ### Removed

README.md

@@ -371,12 +371,12 @@ We recommend to start with a minimal installation, and install additional depend
 
 For ease of installation of these extensions, we provide `pip` wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
 
-#### PyTorch 2.4
+#### PyTorch 2.5
 
-To install the binaries for PyTorch 2.4.0, simply run
+To install the binaries for PyTorch 2.5.0, simply run
 
 ```
-pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.4.0+${CUDA}.html
+pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.5.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu121`, or `cu124` depending on your PyTorch installation.
@@ -387,23 +387,23 @@ where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu121`, or `cu124`
 | **Windows** | ✅    | ✅      | ✅      | ✅      |
 | **macOS**   | ✅    |         |         |         |
 
-#### PyTorch 2.3
+#### PyTorch 2.4
 
-To install the binaries for PyTorch 2.3.0, simply run
+To install the binaries for PyTorch 2.4.0, simply run
 
 ```
-pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+${CUDA}.html
+pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.4.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu121`, or `cu124` depending on your PyTorch installation.
 
-|             | `cpu` | `cu118` | `cu121` |
-| ----------- | ----- | ------- | ------- |
-| **Linux**   | ✅    | ✅      | ✅      |
-| **Windows** | ✅    | ✅      | ✅      |
-| **macOS**   | ✅    |         |         |
+|             | `cpu` | `cu118` | `cu121` | `cu124` |
+| ----------- | ----- | ------- | ------- | ------- |
+| **Linux**   | ✅    | ✅      | ✅      | ✅      |
+| **Windows** | ✅    | ✅      | ✅      | ✅      |
+| **macOS**   | ✅    |         |         |         |
 
-**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2, PyTorch 1.11.0, PyTorch 1.12.0/1.12.1, PyTorch 1.13.0/1.13.1, PyTorch 2.0.0/2.0.1, PyTorch 2.1.0/2.1.1/2.1.2, and PyTorch 2.2.0/2.2.1/2.2.2 (following the same procedure).
+**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2, PyTorch 1.11.0, PyTorch 1.12.0/1.12.1, PyTorch 1.13.0/1.13.1, PyTorch 2.0.0/2.0.1, PyTorch 2.1.0/2.1.1/2.1.2, PyTorch 2.2.0/2.2.1/2.2.2, and PyTorch 2.3.0/2.3.1 (following the same procedure).
 **For older versions, you might need to explicitly specify the latest supported version number** or install via `pip install --no-index` in order to prevent a manual installation from source.
 You can look up the latest supported version number [here](https://data.pyg.org/whl).
 

docker/Dockerfile.xpu

@@ -27,5 +27,5 @@ RUN echo "source /opt/intel/oneapi/setvars.sh --force" >> /root/.bashrc
 
 # Install PyG
 RUN pip install ninja wheel ogb && pip install git+https://github.com/pyg-team/pyg-lib.git && \
-    pip install torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.4.0+cpu.html && \
+    pip install torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.5.0+cpu.html && \
     pip install torch_geometric

docs/source/install/installation.rst

@@ -72,7 +72,7 @@ For ease of installation of these extensions, we provide :obj:`pip` wheels for t
    .. code-block:: none
 
       python -c "import torch; print(torch.__version__)"
-      >>> 2.4.0
+      >>> 2.5.0
 
 #. Find the CUDA version :pytorch:`PyTorch` was installed with:
 
@@ -89,26 +89,27 @@ For ease of installation of these extensions, we provide :obj:`pip` wheels for t
 
    where :obj:`${TORCH}` and :obj:`${CUDA}` should be replaced by the specific :pytorch:`PyTorch` and CUDA versions, respectively:
 
+   * :pytorch:`PyTorch` 2.4: :obj:`${TORCH}=2.5.0` and :obj:`${CUDA}=cpu|cu118|cu121|cu124`
    * :pytorch:`PyTorch` 2.4: :obj:`${TORCH}=2.4.0` and :obj:`${CUDA}=cpu|cu118|cu121|cu124`
    * :pytorch:`PyTorch` 2.3: :obj:`${TORCH}=2.3.0` and :obj:`${CUDA}=cpu|cu118|cu121`
    * :pytorch:`PyTorch` 2.2: :obj:`${TORCH}=2.2.0` and :obj:`${CUDA}=cpu|cu118|cu121`
    * :pytorch:`PyTorch` 2.1: :obj:`${TORCH}=2.1.0` and :obj:`${CUDA}=cpu|cu118|cu121`
    * :pytorch:`PyTorch` 2.0: :obj:`${TORCH}=2.0.0` and :obj:`${CUDA}=cpu|cu117|cu118`
    * :pytorch:`PyTorch` 1.13: :obj:`${TORCH}=1.13.0` and :obj:`${CUDA}=cpu|cu116|cu117`
 
-   For example, for :pytorch:`PyTorch` 2.4.* and CUDA 12.4, type:
+   For example, for :pytorch:`PyTorch` 2.5.* and CUDA 12.4, type:
 
    .. code-block:: none
 
-      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.4.0+cu124.html
+      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.5.0+cu124.html
 
-   For example, for :pytorch:`PyTorch` 2.3.* and CUDA 11.8, type:
+   For example, for :pytorch:`PyTorch` 2.4.* and CUDA 11.8, type:
 
    .. code-block:: none
 
-      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+cu118.html
+      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.4.0+cu118.html
 
-**Note:** Binaries of older versions are also provided for :pytorch:`PyTorch` 1.4.0, 1.5.0, 1.6.0, 1.7.0/1.7.1, 1.8.0/1.8.1, 1.9.0, 1.10.0/1.10.1/1.10.2, 1.11.0, 1.12.0/1.12.1, 1.13.0/1.13.1, 2.0.0/2.0.1, 2.1.0/2.1.1/2.1.2, and 2.2.0/2.2.1/2.2.2 (following the same procedure).
+**Note:** Binaries of older versions are also provided for :pytorch:`PyTorch` 1.4.0, 1.5.0, 1.6.0, 1.7.0/1.7.1, 1.8.0/1.8.1, 1.9.0, 1.10.0/1.10.1/1.10.2, 1.11.0, 1.12.0/1.12.1, 1.13.0/1.13.1, 2.0.0/2.0.1, 2.1.0/2.1.1/2.1.2, 2.2.0/2.2.1/2.2.2, and 2.3.0/2.3.1 (following the same procedure).
 **For older versions, you need to explicitly specify the latest supported version number** or install via :obj:`pip install --no-index` in order to prevent a manual installation from source.
 You can look up the latest supported version number `here <https://data.pyg.org/whl>`__.
 

docs/source/install/quick-start.html

@@ -75,9 +75,9 @@
 
 <script>
   var torchList = [
+    ['torch-2.5.0', 'PyTorch 2.5.*'],
     ['torch-2.4.0', 'PyTorch 2.4.*'],
     ['torch-2.3.0', 'PyTorch 2.3.*'],
-    ['torch-2.2.0', 'PyTorch 2.2.*'],
   ];
 
   var osList = [
@@ -113,7 +113,7 @@
       $("#command pre").text('# macOS binaries do not support CUDA');
     }
 
-    else if (torch != "torch-2.4.0" && cuda == "cu124") {
+    else if (torch == "torch-2.3.0" && cuda == "cu124") {
       $("#command pre").text('# PyTorch version does not support CUDA 12.4');
     }
 

examples/multi_gpu/distributed_sampling.py

@@ -1,4 +1,5 @@
 import os
+from math import ceil
 
 import torch
 import torch.distributed as dist
@@ -56,11 +57,11 @@ def run(rank, world_size, dataset):
 
     # Split indices into `world_size` many chunks:
     train_idx = data.train_mask.nonzero(as_tuple=False).view(-1)
-    train_idx = train_idx.split(train_idx.size(0) // world_size)[rank]
+    train_idx = train_idx.split(ceil(train_idx.size(0) / world_size))[rank]
     val_idx = data.val_mask.nonzero(as_tuple=False).view(-1)
-    val_idx = val_idx.split(val_idx.size(0) // world_size)[rank]
+    val_idx = val_idx.split(ceil(val_idx.size(0) / world_size))[rank]
     test_idx = data.val_mask.nonzero(as_tuple=False).view(-1)
-    test_idx = test_idx.split(test_idx.size(0) // world_size)[rank]
+    test_idx = test_idx.split(ceil(test_idx.size(0) / world_size))[rank]
 
     kwargs = dict(
         data=data,

examples/multi_gpu/distributed_sampling_multinode.py

@@ -1,5 +1,6 @@
 import copy
 import os
+from math import ceil
 
 import torch
 import torch.distributed as dist
@@ -86,7 +87,7 @@ def run(world_size: int, rank: int, local_rank: int):
 
     # Split training indices into `world_size` many chunks:
     train_idx = data.train_mask.nonzero(as_tuple=False).view(-1)
-    train_idx = train_idx.split(train_idx.size(0) // world_size)[rank]
+    train_idx = train_idx.split(ceil(train_idx.size(0) / world_size))[rank]
 
     kwargs = dict(batch_size=1024, num_workers=4, persistent_workers=True)
     train_loader = NeighborLoader(

examples/multi_gpu/pcqm4m_ogb.py

@@ -1,6 +1,7 @@
 # Code adapted from OGB.
 # https://github.com/snap-stanford/ogb/tree/master/examples/lsc/pcqm4m-v2
 import argparse
+import math
 import os
 
 import torch
@@ -433,7 +434,8 @@ def run(rank, dataset, args):
         train_idx = split_idx["train"]
 
     if num_devices > 1:
-        train_idx = train_idx.split(train_idx.size(0) // num_devices)[rank]
+        num_splits = math.ceil(train_idx.size(0) / num_devices)
+        train_idx = train_idx.split(num_splits)[rank]
 
     if args.train_subset:
         subset_ratio = 0.1