Extend nightly tests to include different PyTorch versions (#7073)

pyg-team · Mar 29, 2023 · 692a8ce · 692a8ce
1 parent 306e790
commit 692a8ce
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Showing 10 changed files with 28 additions and 9 deletions.
diff --git a/.github/actions/setup/action.yml b/.github/actions/setup/action.yml
@@ -47,14 +47,14 @@ runs:
       shell: bash
 
     - name: Install extension packages
-      if: ${{ inputs.full_install == 'true' }}
+      if: ${{ inputs.full_install == 'true' && inputs.torch-version != 'nightly' }}
       run: |
         pip install torchvision==${{ inputs.torchvision-version }} --extra-index-url https://download.pytorch.org/whl/${{ inputs.cuda-version }}
         pip install torch-scatter torch-sparse torch-cluster torch-spline-conv -f https://data.pyg.org/whl/torch-${{ inputs.torch-version }}+${{ inputs.cuda-version }}.html
       shell: bash
 
     - name: Install pyg-lib  # pyg-lib is currently only available on Linux.
-      if: ${{ inputs.full_install == 'true' && runner.os == 'Linux' }}
+      if: ${{ inputs.full_install == 'true' && inputs.torch-version != 'nightly' && runner.os == 'Linux' }}
       run: |
         pip install pyg-lib -f https://data.pyg.org/whl/nightly/torch-${{ inputs.torch-version }}+${{ inputs.cuda-version }}.html
       shell: bash
diff --git a/.github/workflows/full_testing.yml b/.github/workflows/full_testing.yml
@@ -15,7 +15,15 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest]
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.8', '3.10']
+        torch-version: [1.13.0, 2.0.0, nightly]
+        include:
+          - torch-version: 1.13.0
+            torchvision-version: 0.14.0
+          - torch-version: 2.0.0
+            torchvision-version: 0.15.0
+          - torch-version: nightly
+            torchvision-version: nightly
 
     steps:
       - name: Checkout repository
@@ -25,6 +33,8 @@ jobs:
         uses: ./.github/actions/setup
         with:
           python-version: ${{ matrix.python-version }}
+          torch-version: ${{ matrix.torch-version }}
+          torchvision-version: ${{ matrix.torchvision-version }}
 
       - name: Install graphviz
         if: ${{ runner.os == 'Linux' }}

diff --git a/.github/workflows/latest_testing.yml b/.github/workflows/latest_testing.yml
@@ -37,7 +37,6 @@ jobs:
         uses: ./.github/actions/setup
         with:
           torch-version: nightly
-          full_install: false
 
       - name: Install main package
         if: steps.changed-files-specific.outputs.only_changed != 'true'

diff --git a/test/nn/models/test_graph_unet.py b/test/nn/models/test_graph_unet.py
@@ -1,9 +1,10 @@
 import torch
 
 from torch_geometric.nn import GraphUNet
-from torch_geometric.testing import is_full_test
+from torch_geometric.testing import is_full_test, onlyLinux
 
 
+@onlyLinux  # TODO  (matthias) Investigate CSR @ CSR support on Windows.
 def test_graph_unet():
     model = GraphUNet(16, 32, 8, depth=3)
     out = 'GraphUNet(16, 32, 8, depth=3, pool_ratios=[0.5, 0.5, 0.5])'

diff --git a/test/nn/norm/test_diff_group_norm.py b/test/nn/norm/test_diff_group_norm.py
@@ -24,7 +24,7 @@ def test_diff_group_norm():
 
     if is_full_test():
         jit = torch.jit.script(norm)
-        assert torch.alllclose(jit(x), out)
+        assert torch.allclose(jit(x), out)
 
 
 def test_group_distance_ratio():

diff --git a/test/nn/pool/test_asap.py b/test/nn/pool/test_asap.py
@@ -4,9 +4,10 @@
 import torch
 
 from torch_geometric.nn import ASAPooling, GCNConv, GraphConv
-from torch_geometric.testing import is_full_test, onlyFullTest
+from torch_geometric.testing import is_full_test, onlyFullTest, onlyLinux
 
 
+@onlyLinux  # TODO  (matthias) Investigate CSR @ CSR support on Windows.
 def test_asap():
     in_channels = 16
     edge_index = torch.tensor([[0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3],

diff --git a/test/nn/pool/test_pool.py b/test/nn/pool/test_pool.py
@@ -4,10 +4,11 @@
 from torch import Tensor
 
 from torch_geometric.nn import radius_graph
-from torch_geometric.testing import onlyFullTest
+from torch_geometric.testing import onlyFullTest, withPackage
 
 
 @onlyFullTest
+@withPackage('torch_cluster')
 def test_radius_graph_jit():
     class Net(torch.nn.Module):
         def forward(self, x: Tensor, batch: Optional[Tensor] = None) -> Tensor:

diff --git a/test/transforms/test_add_positional_encoding.py b/test/transforms/test_add_positional_encoding.py
@@ -3,6 +3,7 @@
 import torch
 
 from torch_geometric.data import Data
+from torch_geometric.testing import onlyLinux
 from torch_geometric.transforms import (
     AddLaplacianEigenvectorPE,
     AddRandomWalkPE,
@@ -52,6 +53,7 @@ def test_add_laplacian_eigenvector_pe():
     assert torch.allclose(pe_cluster_2, pe_cluster_2.mean())
 
 
+@onlyLinux  # TODO  (matthias) Investigate CSR @ CSR support on Windows.
 def test_add_random_walk_pe():
     x = torch.randn(6, 4)
     edge_index = torch.tensor([[0, 1, 0, 4, 1, 4, 2, 3, 3, 5],

diff --git a/test/transforms/test_two_hop.py b/test/transforms/test_two_hop.py
@@ -1,9 +1,11 @@
 import torch
 
 from torch_geometric.data import Data
+from torch_geometric.testing import onlyLinux
 from torch_geometric.transforms import TwoHop
 
 
+@onlyLinux  # TODO  (matthias) Investigate CSR @ CSR support on Windows.
 def test_two_hop():
     transform = TwoHop()
     assert str(transform) == 'TwoHop()'

diff --git a/torch_geometric/nn/pool/asap.py b/torch_geometric/nn/pool/asap.py
@@ -145,7 +145,10 @@ def forward(
         S = S.index_select(1, perm).to_sparse_csr()
         A = S.t().to_sparse_csr() @ (A @ S)
 
-        edge_index, edge_weight = to_edge_index(A)
+        if edge_weight is None:
+            edge_index, _ = to_edge_index(A)
+        else:
+            edge_index, edge_weight = to_edge_index(A)
 
         if self.add_self_loops:
             edge_index, edge_weight = add_remaining_self_loops(