PyTorch 1.12 support (pyg-team#4975)

* Fix norm in examples and dmon_pool * changelog * update * PyTorch 1.12 support * changelog * updaet * reset * update * update Co-authored-by: Guohao Li <lighaime@gmail.com>
GericoVi · Jul 13, 2022 · 6522693 · 6522693
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diff --git a/.github/workflows/building_pyg_conda.yml b/.github/workflows/building_pyg_conda.yml
@@ -12,27 +12,25 @@ jobs:
       matrix:
         os: [ubuntu-18.04, macos-10.15, windows-2019]
         python-version: ['3.7', '3.8', '3.9', '3.10']
-        torch-version: [1.10.0, 1.11.0]
-        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115']
+        torch-version: [1.11.0, 1.12.0]
+        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115', 'cu116']
         exclude:
-          - torch-version: 1.10.0
+          - torch-version: 1.11.0
+            cuda-version: 'cu116'
+          - torch-version: 1.12.0
             cuda-version: 'cu115'
-          - torch-version: 1.10.0
-            python-version: '3.10'
-          - os: windows-2019
-            torch-version: 1.11.0
-            cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu113'
           - os: macos-10.15
             cuda-version: 'cu115'
-          # There is a weird `glibc=2.27` bug going on for this combination:
-          - os: ubuntu-18.04
-            python-version: '3.10'
-          - os: ubuntu-18.04
-            cuda-version: 'cu115'
+          - os: macos-10.15
+            cuda-version: 'cu116'
+          - os: windows-2019
+            cuda-version: 'cu102'
+          - os: windows-2019  # Complains about CUDA mismatch.
+            python-version: '3.7'
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/building_rusty1s_conda.yml b/.github/workflows/building_rusty1s_conda.yml
@@ -12,27 +12,25 @@ jobs:
       matrix:
         os: [ubuntu-18.04, macos-10.15, windows-2019]
         python-version: ['3.7', '3.8', '3.9', '3.10']
-        torch-version: [1.10.0, 1.11.0]
-        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115']
+        torch-version: [1.11.0, 1.12.0]
+        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115', 'cu116']
         exclude:
-          - torch-version: 1.10.0
+          - torch-version: 1.11.0
+            cuda-version: 'cu116'
+          - torch-version: 1.12.0
             cuda-version: 'cu115'
-          - torch-version: 1.10.0
-            python-version: '3.10'
-          - os: windows-2019
-            torch-version: 1.11.0
-            cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu113'
           - os: macos-10.15
             cuda-version: 'cu115'
-          # There is a weird `glibc=2.27` bug going on for this combination:
-          - os: ubuntu-18.04
-            python-version: '3.10'
-          - os: ubuntu-18.04
-            cuda-version: 'cu115'
+          - os: macos-10.15
+            cuda-version: 'cu116'
+          - os: windows-2019
+            cuda-version: 'cu102'
+          - os: windows-2019  # Complains about CUDA mismatch.
+            python-version: '3.7'
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/documentation.yml b/.github/workflows/documentation.yml
@@ -15,7 +15,7 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         python-version: [3.8]
-        torch-version: [1.11.0]
+        torch-version: [1.12.0]
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml
@@ -16,10 +16,10 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         python-version: [3.9]
-        torch-version: [1.11.0]
+        torch-version: [1.12.0]
         include:
-          - torch-version: 1.11.0
-            torchvision-version: 0.12.0
+          - torch-version: 1.12.0
+            torchvision-version: 0.13.0
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/full_testing.yml b/.github/workflows/full_testing.yml
@@ -15,11 +15,11 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest]
-        python-version: ['3.7', '3.8', '3.9']
-        torch-version: [1.10.0]
+        python-version: ['3.7', '3.8', '3.9', '3.10']
+        torch-version: [1.12.0]
         include:
-          - torch-version: 1.10.0
-            torchvision-version: 0.11.1
+          - torch-version: 1.12.0
+            torchvision-version: 0.13.0
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/install.yml b/.github/workflows/install.yml
@@ -15,7 +15,7 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         python-version: [3.9]
-        torch-version: [1.11.0]
+        torch-version: [1.12.0]
 
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
@@ -16,12 +16,12 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         python-version: [3.9]
-        torch-version: [1.10.0, 1.11.0]
+        torch-version: [1.11.0, 1.12.0]
         include:
-          - torch-version: 1.10.0
-            torchvision-version: 0.11.1
           - torch-version: 1.11.0
             torchvision-version: 0.12.0
+          - torch-version: 1.12.0
+            torchvision-version: 0.13.0
 
     steps:
       - uses: actions/checkout@v3
@@ -37,7 +37,7 @@ jobs:
       - name: Install internal dependencies
         run: |
           pip install torch-scatter -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
-          pip install torch-sparse==0.6.13 -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
+          pip install torch-sparse -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
           pip install torch-cluster -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
           pip install torch-spline-conv -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
 

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -5,6 +5,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [2.0.5] - 2022-MM-DD
 ### Added
+- Added PyTorch 1.12 support  ([#4975](https://github.com/pyg-team/pytorch_geometric/pull/4975))
 - Added `unbatch_edge_index` functionality for splitting an `edge_index` tensor according to a `batch` vector ([#4903](https://github.com/pyg-team/pytorch_geometric/pull/4903))
 - Added node-wise normalization mode in `LayerNorm` ([#4944](https://github.com/pyg-team/pytorch_geometric/pull/4944))
 - Added support for `normalization_resolver` ([#4926](https://github.com/pyg-team/pytorch_geometric/pull/4926), [#4951](https://github.com/pyg-team/pytorch_geometric/pull/4951), [#4958](https://github.com/pyg-team/pytorch_geometric/pull/4958), [#4959](https://github.com/pyg-team/pytorch_geometric/pull/4959))

diff --git a/README.md b/README.md
@@ -357,23 +357,25 @@ Given that you have [PyTorch >= 1.8.0 installed](https://pytorch.org/get-started
 conda install pyg -c pyg
 ```
 
+**Note:** Conda packages are not published for PyTorch 1.12 yet.
+
 ### Pip Wheels
 
 We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
 
-#### PyTorch 1.11
+#### PyTorch 1.12
 
-To install the binaries for PyTorch 1.11.0, simply run
+To install the binaries for PyTorch 1.12.0, simply run
 
 ```
-pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
-pip install torch-sparse -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
+pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
+pip install torch-sparse -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
 pip install torch-geometric
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu115` depending on your PyTorch installation (`torch.version.cuda`).
+where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu116` depending on your PyTorch installation.
 
-|             | `cpu` | `cu102` | `cu113` | `cu115` |
+|             | `cpu` | `cu102` | `cu113` | `cu116` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
 | **Windows** | ✅    |         | ✅      | ✅      |
@@ -382,36 +384,36 @@ where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu115`
 For additional but optional functionality, run
 
 ```
-pip install torch-cluster -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
-pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
+pip install torch-cluster -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
+pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
 ```
 
-#### PyTorch 1.10
+#### PyTorch 1.11
 
-To install the binaries for PyTorch 1.10.0, PyTorch 1.10.1 and 1.10.2, simply run
+To install the binaries for PyTorch 1.11.0, simply run
 
 ```
-pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+${CUDA}.html
-pip install torch-sparse -f https://data.pyg.org/whl/torch-1.10.0+${CUDA}.html
+pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
+pip install torch-sparse -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
 pip install torch-geometric
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu111` or `cu113` depending on your PyTorch installation (`torch.version.cuda`).
+where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu115` depending on your PyTorch installation (`torch.version.cuda`).
 
-|             | `cpu` | `cu102` | `cu111` | `cu113` |
+|             | `cpu` | `cu102` | `cu113` | `cu115` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
-| **Windows** | ✅    | ✅      | ✅      | ✅      |
+| **Windows** | ✅    |         | ✅      | ✅      |
 | **macOS**   | ✅    |         |         |         |
 
 For additional but optional functionality, run
 
 ```
-pip install torch-cluster -f https://data.pyg.org/whl/torch-1.10.0+${CUDA}.html
-pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.10.0+${CUDA}.html
+pip install torch-cluster -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
+pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
 ```
 
-**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 and PyTorch 1.9.0 (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, and PyTorch 1.10.0/1.10.1/1.10.2 (following the same procedure).
 For older versions, you might need to explicitly specify the latest supported version number in order to prevent a manual installation from source.
 You can look up the latest supported version number [here](https://data.pyg.org/whl).
 

diff --git a/docs/source/notes/installation.rst b/docs/source/notes/installation.rst
@@ -23,19 +23,21 @@ Given that you have `PyTorch >= 1.8.0 installed <https://pytorch.org/get-started
 
     conda install pyg -c pyg
 
+**Note:** Conda packages are not published for PyTorch 1.12 yet.
+
 Installation via Pip Wheels
 ---------------------------
 
 We have outsourced a lot of functionality of PyG to other packages, which needs to be installed in advance.
 These packages come with their own CPU and GPU kernel implementations based on the `PyTorch C++/CUDA extension interface <https://github.com/pytorch/extension-cpp/>`_.
 We provide pip wheels for these packages for all major OS/PyTorch/CUDA combinations, see `here <https://data.pyg.org/whl>`__:
 
-#. Ensure that at least PyTorch 1.10.0 is installed:
+#. Ensure that at least PyTorch 1.11.0 is installed:
 
     .. code-block:: none
 
         python -c "import torch; print(torch.__version__)"
-        >>> 1.11.0
+        >>> 1.12.0
 
 #. Find the CUDA version PyTorch was installed with:
 
@@ -52,21 +54,21 @@ We provide pip wheels for these packages for all major OS/PyTorch/CUDA combinati
          pip install torch-sparse -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html
          pip install torch-geometric
 
-    where :obj:`${CUDA}` and :obj:`${TORCH}` should be replaced by the specific CUDA version (:obj:`cpu`, :obj:`cu102`, :obj:`cu113`, :obj:`cu115`) and PyTorch version (:obj:`1.10.0`, :obj:`1.11.0`), respectively.
-    For example, for PyTorch 1.11.* and CUDA 11.3, type:
+    where :obj:`${CUDA}` and :obj:`${TORCH}` should be replaced by the specific CUDA version (:obj:`cpu`, :obj:`cu102`, :obj:`cu113`, :obj:`cu115`) and PyTorch version (:obj:`1.11.0`, :obj:`1.12.0`), respectively.
+    For example, for PyTorch 1.12.* and CUDA 11.6, type:
 
     .. code-block:: none
 
-         pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+cu113.html
-         pip install torch-sparse -f https://data.pyg.org/whl/torch-1.11.0+cu113.html
+         pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.0+cu116.html
+         pip install torch-sparse -f https://data.pyg.org/whl/torch-1.12.0+cu116.html
          pip install torch-geometric
 
-    For PyTorch 1.10.* and CUDA 10.2, type:
+    For PyTorch 1.11.* and CUDA 11.3, type:
 
     .. code-block:: none
 
-         pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+cu102.html
-         pip install torch-sparse -f https://data.pyg.org/whl/torch-1.10.0+cu102.html
+         pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+cu113.html
+         pip install torch-sparse -f https://data.pyg.org/whl/torch-1.11.0+cu113.html
          pip install torch-geometric
 
 #. Install additional packages *(optional)*:
@@ -80,7 +82,7 @@ We provide pip wheels for these packages for all major OS/PyTorch/CUDA combinati
 
     following the same procedure as mentioned above.
 
-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 and PyTorch 1.9.0 (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, and PyTorch 1.10.0/1.10.1/1.10.2 (following the same procedure).
 **For older versions, you need to explicitly specify the latest supported version number** in order to prevent a manual installation from source.
 You can look up the latest supported version number `here <https://data.pyg.org/whl>`__.
 

diff --git a/docs/source/notes/quick-start.html b/docs/source/notes/quick-start.html
@@ -75,8 +75,8 @@
 
 <script>
   var torchList = [
+    ['torch-1.12.0', 'PyTorch 1.12.*'],
     ['torch-1.11.0', 'PyTorch 1.11.*'],
-    ['torch-1.10.0', 'PyTorch 1.10.*'],
   ];
 
   var osList = [
@@ -94,6 +94,7 @@
     ['cu102', '10.2'],
     ['cu113', '11.3'],
     ['cu115', '11.5'],
+    ['cu116', '11.6'],
     ['cpu', 'CPU'],
   ];
 
@@ -112,12 +113,24 @@
       $("#command pre").text('# macOS binaries do not support CUDA');
     }
 
+    else if (torch == "torch-1.12.0" && cuda == "cu102" && os == "windows") {
+      $("#command pre").text('# PyTorch 1.12.* Windows binaries do not support CUDA 10.2');
+    }
+
     else if (torch == "torch-1.11.0" && cuda == "cu102" && os == "windows") {
       $("#command pre").text('# PyTorch 1.11.* Windows binaries do not support CUDA 10.2');
     }
 
-    else if (torch == "torch-1.10.0" && cuda == "cu115") {
-      $("#command pre").text('# PyTorch 1.10.* binaries do not support CUDA 11.5');
+    else if (torch == "torch-1.12.0" && cuda == "cu115") {
+      $("#command pre").text('# PyTorch 1.12.* binaries do not support CUDA 11.5');
+    }
+
+    else if (torch == "torch-1.11.0" && cuda == "cu116") {
+      $("#command pre").text('# PyTorch 1.11.* binaries do not support CUDA 11.6');
+    }
+
+    else if (package == "conda" && torch == "torch-1.12.0") {
+      $("#command pre").text('# Conda packages are not published for PyTorch 1.12 yet');
     }
 
     else if (package == "conda") {

diff --git a/test/graphgym/test_config_store.py b/test/graphgym/test_config_store.py
@@ -56,7 +56,6 @@ def test_config_store():
     assert cfg.model.act_kwargs is None
 
     # Check `cfg.optimizer`:
-    assert len(cfg.optimizer) in {6, 7}  # Arguments changed across 1.10/1.11
     assert cfg.optimizer._target_.split('.')[-1] == 'Adam'
     assert cfg.optimizer.lr == 0.001
     assert cfg.optimizer.betas == [0.9, 0.999]
@@ -67,7 +66,6 @@ def test_config_store():
         assert not cfg.optimizer.maximize
 
     # Check `cfg.lr_scheduler`:
-    assert len(cfg.lr_scheduler) == 10
     assert cfg.lr_scheduler._target_.split('.')[-1] == 'ReduceLROnPlateau'
     assert cfg.lr_scheduler.mode == 'min'
     assert cfg.lr_scheduler.factor == 0.1