Merge pull request #61 from SherylHYX/K_param_docs

K parameter documentation updates

.github/workflows/main.yml

@@ -15,10 +15,10 @@ jobs:
     strategy:
       matrix:
         python-version: [3.7, 3.8, 3.9]
-        os: [windows-latest, ubuntu-latest]
-        torch-version: [2.0.0]
+        os: [ubuntu-latest]
+        torch-version: [2.3.0]
         include:
-          - torch-version: 2.0.0
+          - torch-version: 2.3.0
 
     steps:
     - uses: actions/checkout@v2
@@ -37,9 +37,9 @@ jobs:
     - run: which python
     - name: Run installation.
       run: |
-        python -m pip install torch==2.0.0 torchvision torchaudio -f https://download.pytorch.org/whl/cpu/torch_stable.html
-        python -m pip install torch-scatter -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
-        python -m pip install torch-sparse -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
+        python -m pip install torch==2.3.0 torchvision torchaudio -f https://download.pytorch.org/whl/cpu/torch_stable.html
+        python -m pip install torch-scatter -f https://data.pyg.org/whl/torch-2.3.0+cpu.html
+        python -m pip install torch-sparse -f https://data.pyg.org/whl/torch-2.3.0+cpu.html
         python -m pip install torch-geometric
         python -m pip install sphinx sphinx_rtd_theme
         python -m pip install -e .[test]

torch_geometric_signed_directed/nn/directed/MagNetConv.py

@@ -19,7 +19,7 @@ class MagNetConv(MessagePassing):
     Args:
         in_channels (int): Size of each input sample.
         out_channels (int): Size of each output sample.
-        K (int): Chebyshev filter size :math:`K`.
+        K (int): Order of the Chebyshev polynomial minus 1, i.e., Chebyshev filter size :math:`K`.
         q (float, optional): Initial value of the phase parameter, 0 <= q <= 0.25. Default: 0.25.
         trainable_q (bool, optional): whether to set q to be trainable or not. (default: :obj:`False`)
         normalization (str, optional): The normalization scheme for the magnetic

torch_geometric_signed_directed/nn/directed/MagNet_link_prediction.py

@@ -15,7 +15,7 @@ class MagNet_link_prediction(nn.Module):
     Args:
         num_features (int): Size of each input sample.
         hidden (int, optional): Number of hidden channels.  Default: 2.
-        K (int, optional): Order of the Chebyshev polynomial.  Default: 2.
+        K (int, optional): Order of the Chebyshev polynomial minus 1, i.e., Chebyshev filter size :math:`K`.  Default: 2.
         q (float, optional): Initial value of the phase parameter, 0 <= q <= 0.25. Default: 0.25.
         label_dim (int, optional): Number of output classes.  Default: 2.
         activation (bool, optional): whether to use activation function or not. (default: :obj:`True`)

torch_geometric_signed_directed/nn/directed/MagNet_node_classification.py

@@ -15,7 +15,7 @@ class MagNet_node_classification(nn.Module):
     Args:
         num_features (int): Size of each input sample.
         hidden (int, optional): Number of hidden channels.  Default: 2.
-        K (int, optional): Order of the Chebyshev polynomial.  Default: 2.
+        K (int, optional): Order of the Chebyshev polynomial minus 1, i.e., Chebyshev filter size :math:`K`.  Default: 2.
         q (float, optional): Initial value of the phase parameter, 0 <= q <= 0.25. Default: 0.25.
         label_dim (int, optional): Number of output classes.  Default: 2.
         activation (bool, optional): whether to use activation function or not. (default: :obj:`False`)

torch_geometric_signed_directed/nn/general/MSConv.py

@@ -16,7 +16,7 @@ class MSConv(MessagePassing):
     Args:
         in_channels (int): Size of each input sample.
         out_channels (int): Size of each output sample.
-        K (int): Chebyshev filter size :math:`K`.
+        K (int): Order of the Chebyshev polynomial minus 1, i.e., Chebyshev filter size :math:`K`.
         q (float, optional): Initial value of the phase parameter, 0 <= q <= 0.25. Default: 0.25.
         trainable_q (bool, optional): whether to set q to be trainable or not. (default: :obj:`False`)
         normalization (str, optional): The normalization scheme for the magnetic

torch_geometric_signed_directed/nn/general/MSGNN.py

@@ -14,7 +14,7 @@ class MSGNN_link_prediction(nn.Module):
     Args:
         num_features (int): Size of each input sample.
         hidden (int, optional): Number of hidden channels.  Default: 2.
-        K (int, optional): Order of the Chebyshev polynomial.  Default: 2.
+        K (int, optional): Order of the Chebyshev polynomial minus 1, i.e., Chebyshev filter size :math:`K`.  Default: 2.
         q (float, optional): Initial value of the phase parameter, 0 <= q <= 0.25. Default: 0.25.
         label_dim (int, optional): Number of output classes.  Default: 2.
         activation (bool, optional): whether to use activation function or not. (default: :obj:`True`)