Merge pull request #308 from AIM-Harvard/saliency_patch

Add saliency notebook

.github/workflows/build.yml

@@ -26,7 +26,7 @@ jobs:
       run: make poetry-download
 
     - name: Set up cache
-      uses: actions/cache@v2.1.6
+      uses: actions/cache@v4
       with:
         path: .venv
         key: venv-${{ matrix.python-version }}-${{ hashFiles('pyproject.toml') }}-${{ hashFiles('poetry.lock') }}

.github/workflows/publish.yml

@@ -2,7 +2,7 @@ name: Auto Publish
 on:
   push:
     branches:
-      - master
+      - main
 
 jobs:
   build:
@@ -12,28 +12,32 @@ jobs:
         - name: Set up Python
           uses: actions/[email protected]
           with:
-            python-version: 3.8
+            python-version: 3.9
 
         - name: Install poetry
           run: make setup
-
+
+        - name: Install poeblix for version freezing
+          run: poetry self add poeblix@latest
+
         - name: Bump version
           run: |
             poetry version prerelease
-    
 
-        - name: Commit & push changes
+        - name: Commit changes
           run: |
             git config --local user.email "[email protected]"
             git config --local user.name "GitHub Action"
             git add .
             git commit -m "Bump version" || echo "No changes to commit"
-            git push
-   
-        - name: Build and publish to pypi
-          uses: JRubics/[email protected]
+
+        - name: Push changes
+          run: git push
+
+        - name: Build with lockfile versions
+          run: poetry blixbuild --only-lock
+
+        - name: Publish distribution 📦 to PyPI
+          uses: pypa/gh-action-pypi-publish@release/v1
           with:
-            python_version: 3.8
-            pypi_token: ${{ secrets.PYPI_TOKEN }}
-            allow_poetry_pre_release: "yes"
-            ignore_dev_requirements: "yes"
+            password: ${{ secrets.PYPI_TOKEN }}

Makefile

@@ -65,8 +65,8 @@ mypy:
 .PHONY: check-safety
 check-safety:
 	poetry check
-	poetry run safety check --full-report --ignore 51457 --ignore 67599
-	poetry run bandit -c pyproject.toml -ll --recursive fmcib tests
+	poetry run safety check --full-report --ignore 51457 --ignore 67599 --ignore 70612
+	poetry run bandit -c pyproject.toml -ll --recursive fmcib tests 
 
 .PHONY: lint
 lint: test check-codestyle mypy check-safety

experiments/adaptation/fmcib_finetune.yaml

@@ -42,13 +42,17 @@ system:
     postprocessing:
       metrics:
         pred:
-          - "$lambda x: torch.softmax(x, 1)" # Note: Change to $lambda x: torch.sigmoid(x) for Task 2 and Task 3    
-      # criterion:
-      #   target: # Note: Uncomment for Task 2 and Task 3
-      #     - "$lambda x: x.float()" 
+          - "$lambda x: torch.softmax(x, 1)" # Note: Change to $lambda x: torch.sigmoid(x) for Task 2 and Task 3
+        # target:  # Note: Uncomment for Task 2 and Task 3
+        #   - "$lambda x: x.long()"
+      # criterion: # Note: Uncomment for Task 2 and Task 3
+      #   pred:
+      #     - "$lambda x: x.squeeze(1)"
+      #   target: 
+      #     - "$lambda x: x.float()"
 
     criterion:
-        _target_: torch.nn.CrossEntropyLoss # Note: Change to torch.nn.BCEWithLogitsLoss for Task 2 and Task 3
+      _target_: torch.nn.CrossEntropyLoss # Note: Change to torch.nn.BCEWithLogitsLoss for Task 2 and Task 3
 
     optimizer:
         _target_: torch.optim.Adam
@@ -66,7 +70,7 @@ system:
       train: 
         - _target_: torchmetrics.AveragePrecision
           task: multiclass # Note: Change to `binary` for Task 2 and Task 3 and remove num_classes below
-          num_classes: 8 
+          num_classes: 8
         - _target_: torchmetrics.AUROC
           task: multiclass # Note: Change to `binary` for Task 2 and Task 3 and remove num_classes below
           num_classes: 8

fmcib/models/load_model.py

@@ -96,7 +96,7 @@ def load(self, weights):
 
         Raises the appropriate warnings and logs informational messages.
         """
-        pretrained_model = torch.load(weights, map_location=self.device)
+        pretrained_model = torch.load(weights, map_location=self.device, weights_only=True)
 
         if "trunk_state_dict" in pretrained_model:  # Loading ViSSL pretrained model
             trained_trunk = pretrained_model["trunk_state_dict"]