fix for pytorch 1.13.1 (#9)

* fix for pytorch 1.13.1

* lint

* nbconvert dependency

* update gh actions

.github/workflows/deploy-guide.yml

@@ -14,10 +14,10 @@ jobs:
   deploy-guide:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python 3.8
-      uses: actions/setup-python@v1
+      uses: actions/setup-python@v4
       with:
         python-version: 3.8
 
@@ -28,7 +28,7 @@ jobs:
         unzip train.zip -d data-trajnet
 
     - name: Install ffmpeg
-      uses: FedericoCarboni/setup-ffmpeg@v1
+      uses: FedericoCarboni/setup-ffmpeg@v2
       id: setup-ffmpeg
     - name: ffmpeg codecs
       run: ffmpeg -codecs

.github/workflows/pypi-deploy.yml

@@ -19,11 +19,11 @@ jobs:
     name: Build source distribution
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v4
         name: Install Python
         with:
           python-version: '3.7'
@@ -38,7 +38,7 @@ jobs:
       - name: Build sdist
         run: python setup.py sdist
 
-      - uses: actions/upload-artifact@v2
+      - uses: actions/upload-artifact@v3
         with:
           path: dist/*.tar.gz
 
@@ -50,12 +50,12 @@ jobs:
     # alternatively, to publish when a GitHub Release is created, use the following rule:
     if: github.event_name == 'release' && github.event.action == 'published'
     steps:
-      - uses: actions/download-artifact@v2
+      - uses: actions/download-artifact@v3
         with:
           name: artifact
           path: dist
 
-      - uses: pypa/gh-action-pypi-publish@master
+      - uses: pypa/gh-action-pypi-publish@release/v1
         with:
           user: __token__
           password: ${{ secrets.PYPI_TOKEN }}

.github/workflows/tests.yml

@@ -9,10 +9,6 @@ jobs:
     strategy:
       matrix:
         include:
-          - os: ubuntu-latest
-            python: 3.6
-            torch: 1.9.0+cpu
-            torch-source: https://download.pytorch.org/whl/torch_stable.html
           - os: ubuntu-latest
             python: 3.7
             torch: 1.9.0+cpu
@@ -26,6 +22,10 @@ jobs:
             python: 3.9
             torch: 1.9.0+cpu
             torch-source: https://download.pytorch.org/whl/torch_stable.html
+          - os: ubuntu-latest
+            python: "3.10"
+            torch: 1.13.1+cpu
+            torch-source: https://download.pytorch.org/whl/torch_stable.html
           - os: macos-11
             python: 3.7
             torch: 1.9.0
@@ -50,7 +50,7 @@ jobs:
     steps:
     - run: ls -n /Applications/ | grep Xcode*
       if: matrix.os == 'macos-11'
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Data setup
       if: matrix.slow
       run: |
@@ -59,7 +59,7 @@ jobs:
         unzip train.zip -d data-trajnet
     - name: Set up Python ${{ matrix.python }}
       if: ${{ !matrix.conda }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python }}
     - name: Set up Conda

setup.py

@@ -26,6 +26,7 @@
         'dev': [
             'jupyter-book',
             'matplotlib',
+            'nbconvert',
             'nbstripout',
             'nbval',
             'pycodestyle',

socialforce/potentials/pedped_1d.py

@@ -109,7 +109,12 @@ def norm_r_ab(r_ab):
         zero vector gives nan gradients.
         """
         out = torch.linalg.norm(r_ab, ord=2, dim=2, keepdim=False)
-        torch.diagonal(out)[:] = 0.0
+
+        # only take the upper and lower triangles and leaving the
+        # diagonal at zero and do it in a differentiable way
+        # without inplace ops
+        out = torch.triu(out, diagonal=1) + torch.tril(out, diagonal=-1)
+
         return out
 
 

socialforce/potentials/pedped_2d.py

@@ -175,7 +175,7 @@ def __init__(self, *,
         lin_out = torch.nn.Linear(hidden_units, 1)
 
         # activation_function = torch.nn.Softplus
-        activation_function = lambda: torch.nn.Softplus(beta=5)
+        activation_function = lambda: torch.nn.Softplus(beta=5)  # pylint: disable=unnecessary-lambda-assignment
         self.mlp = torch.nn.Sequential(
             lin_in, activation_function(),
             *[layer for lin in lin_hidden for layer in (lin, activation_function())],

socialforce/trainer.py

@@ -47,7 +47,7 @@ def keep(state1, state2):
             acc = (torch.abs(state1[:, 4:6]) > acc_abs) | (torch.abs(state2[:, 4:6]) > acc_abs)
             acc = torch.any(acc, dim=-1)
             # keep 10% of samples without acc:
-            acc[~acc] = (torch.rand(acc[~acc].shape) < 0.1)
+            acc[~acc] = torch.rand(acc[~acc].shape) < 0.1
             acc[:] = torch.any(acc)  # symmetrize
 
             return valid_state1 & valid_state2 & small_distance & acc

socialforce/trajnet.py

@@ -23,7 +23,7 @@ class Reader:
     """
     def __init__(self, input_file, scene_type=None):
         if scene_type is not None and scene_type not in {'rows', 'paths', 'tags'}:
-            raise Exception('scene_type not supported')
+            raise ValueError('scene_type not supported')
         self.scene_type = scene_type
 
         self.tracks_by_frame = defaultdict(list)
@@ -102,7 +102,7 @@ def paths_to_xy(paths):
     def scene(self, scene_id):
         scene = self.scenes_by_id.get(scene_id)
         if scene is None:
-            raise Exception('scene with that id not found')
+            raise ValueError('scene with that id not found')
 
         frames = range(scene.start, scene.end + 1)
         track_rows = [r