Add PyTorch 2.3 installation guide (#9257)

.github/actions/setup/action.yml

@@ -48,8 +48,8 @@ runs:
         python -c "import torch; print('CUDA:', torch.version.cuda)"
       shell: bash
 
-    - name: Install pyg-lib  # pyg-lib is currently not available on Windows.
-      if: ${{ inputs.torch-version != 'nightly' && inputs.torch-version != '2.3.0' && runner.os != 'Windows' }}
+    - name: Install pyg-lib
+      if: ${{ inputs.torch-version != 'nightly' }}
       run: |
         pip uninstall -y pyg-lib
         pip install --no-index pyg-lib -f https://data.pyg.org/whl/nightly/torch-${{ inputs.torch-version }}+${{ inputs.cuda-version }}.html
@@ -74,7 +74,7 @@ runs:
       shell: bash
 
     - name: Install extension packages
-      if: ${{ inputs.full_install == 'true' && inputs.torch-version != 'nightly' && inputs.torch-version != '2.3.0' && runner.os != 'macOS' }}
+      if: ${{ inputs.full_install == 'true' && inputs.torch-version != 'nightly' }}
       run: |
         pip install scipy
         pip install --no-index --upgrade torch-scatter torch-sparse torch-cluster torch-spline-conv -f https://data.pyg.org/whl/torch-${{ inputs.torch-version }}+${{ inputs.cuda-version }}.html

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 2.2
+#### PyTorch 2.3
 
-To install the binaries for PyTorch 2.2.0, simply run
+To install the binaries for PyTorch 2.3.0, simply run
 
 ```
-pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.2.0+${CUDA}.html
+pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` depending on your PyTorch installation.
@@ -387,12 +387,12 @@ where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` dependin
 | **Windows** | ✅     | ✅       | ✅       |
 | **macOS**   | ✅     |         |         |
 
-#### PyTorch 2.1
+#### PyTorch 2.2
 
-To install the binaries for PyTorch 2.1.0, simply run
+To install the binaries for PyTorch 2.2.0, simply run
 
 ```
-pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+${CUDA}.html
+pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.2.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` depending on your PyTorch installation.
@@ -403,7 +403,7 @@ where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` dependin
 | **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, and PyTorch 2.0.0 (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, 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, and PyTorch 2.1.0/2.1.1/2.1.2 (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).
 

docs/source/install/installation.rst

@@ -67,12 +67,12 @@ For ease of installation of these extensions, we provide :obj:`pip` wheels for t
    Wheels are currently not available for M1/M2/M3 macs.
    Please install the extension packages `from source <installation.html#installation-from-source>`__.
 
-#. Ensure that at least :pytorch:`PyTorch` 1.11.0 is installed:
+#. Ensure that at least :pytorch:`PyTorch` 1.13.0 is installed:
 
    .. code-block:: none
 
       python -c "import torch; print(torch.__version__)"
-      >>> 2.2.0
+      >>> 2.3.0
 
 #. Find the CUDA version :pytorch:`PyTorch` was installed with:
 
@@ -89,24 +89,25 @@ 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` 2.3: :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` 2.2.* and CUDA 12.1, type:
+   For example, for :pytorch:`PyTorch` 2.3.* and CUDA 12.1, type:
 
    .. code-block:: none
 
-      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.2.0+cu121.html
+      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+cu121.html
 
-   For example, for :pytorch:`PyTorch` 2.1.* and CUDA 11.8, type:
+   For example, for :pytorch:`PyTorch` 2.2.* 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-2.1.0+cu118.html
+      pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.2.0+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, and 2.0.0 (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, and 2.1.0/2.1.1/2.1.2 (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-2.3.0', 'PyTorch 2.3.*'],
     ['torch-2.2.0', 'PyTorch 2.2.*'],
     ['torch-2.1.0', 'PyTorch 2.1.*'],
-    ['torch-2.0.0', 'PyTorch 2.0.*'],
   ];
 
   var osList = [
@@ -92,7 +92,6 @@
   ];
 
   var cudaList = [
-    ['cu117', '11.7'],
     ['cu118', '11.8'],
     ['cu121', '12.1'],
     ['cpu', 'CPU'],
@@ -113,23 +112,11 @@
       $("#command pre").text('# macOS binaries do not support CUDA');
     }
 
-    else if (torch == "torch-2.0.0" && cuda == "cu121") {
-      $("#command pre").text('# PyTorch 2.0.* binaries do not support CUDA 12.1');
-    }
-
-    else if (torch == "torch-2.2.0" && cuda == "cu117") {
-      $("#command pre").text('# PyTorch 2.2.* binaries do not support CUDA 11.7');
-    }
-
-    else if (torch == "torch-2.1.0" && cuda == "cu117") {
-      $("#command pre").text('# PyTorch 2.1.* binaries do not support CUDA 11.7');
-    }
-
     else if (package == "conda") {
       $("#command pre").text('conda install pyg -c pyg');
     }
 
-    else if (os == "windows" || os == "mac") {
+    else if ((os == "windows" || os == "mac") && (torch == "torch-2.1.0" || torch == "torch-2.2.0")) {
       $("#command pre").text(`pip install torch_geometric\n\n# Optional dependencies:\npip install torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/${$("#command").attr("torch")}+${$("#command").attr("cuda")}.html`);
     }
 

torch_geometric/datasets/qm9.py

@@ -198,16 +198,16 @@ def download(self) -> None:
 
     def process(self) -> None:
         try:
-            import rdkit
             from rdkit import Chem, RDLogger
             from rdkit.Chem.rdchem import BondType as BT
             from rdkit.Chem.rdchem import HybridizationType
-            RDLogger.DisableLog('rdApp.*')
+            RDLogger.DisableLog('rdApp.*')  # type: ignore
+            WITH_RDKIT = True
 
         except ImportError:
-            rdkit = None
+            WITH_RDKIT = False
 
-        if rdkit is None:
+        if not WITH_RDKIT:
             print(("Using a pre-processed version of the dataset. Please "
                    "install 'rdkit' to alternatively process the raw data."),
                   file=sys.stderr)

torch_geometric/utils/smiles.py

@@ -93,7 +93,7 @@ def from_smiles(smiles: str, with_hydrogen: bool = False,
 
     from torch_geometric.data import Data
 
-    RDLogger.DisableLog('rdApp.*')
+    RDLogger.DisableLog('rdApp.*')  # type: ignore
 
     mol = Chem.MolFromSmiles(smiles)
 
@@ -105,7 +105,7 @@ def from_smiles(smiles: str, with_hydrogen: bool = False,
         Chem.Kekulize(mol)
 
     xs: List[List[int]] = []
-    for atom in mol.GetAtoms():
+    for atom in mol.GetAtoms():  # type: ignore
         row: List[int] = []
         row.append(x_map['atomic_num'].index(atom.GetAtomicNum()))
         row.append(x_map['chirality'].index(str(atom.GetChiralTag())))
@@ -122,7 +122,7 @@ def from_smiles(smiles: str, with_hydrogen: bool = False,
     x = torch.tensor(xs, dtype=torch.long).view(-1, 9)
 
     edge_indices, edge_attrs = [], []
-    for bond in mol.GetBonds():
+    for bond in mol.GetBonds():  # type: ignore
         i = bond.GetBeginAtomIdx()
         j = bond.GetEndAtomIdx()
 
@@ -172,7 +172,7 @@ def to_smiles(data: 'torch_geometric.data.Data',
             data.x[i, 5])])
         atom.SetHybridization(Chem.rdchem.HybridizationType.values[int(
             data.x[i, 6])])
-        atom.SetIsAromatic(int(data.x[i, 7]))
+        atom.SetIsAromatic(bool(data.x[i, 7]))
         mol.AddAtom(atom)
 
     edges = [tuple(i) for i in data.edge_index.t().tolist()]