Merge pull request #172 from XAITK/update-t-v0.12.0

Update to v0.12.0

.github/workflows/.github-quality.yml

@@ -56,6 +56,36 @@ jobs:
         run: poetry run mypy --config-file pyproject.toml src/ tests/
         shell: bash
 
+  pyright:
+    runs-on: ubuntu-latest
+    container: python:3.9
+    steps:
+      - name: Install Git LFS
+        run: |
+          apt-get -qq update
+          apt-get -qq install -y git-lfs
+        shell: bash
+      # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          lfs: true
+      # Cache local python environment artifacts for the current python version
+      # and poetry lockfile hash.
+      - uses: actions/cache@v4
+        id: env-cache
+        with:
+          # Confirmed that the `.local` directory doesn't exist until the
+          # `pip install --user` is invoked below, so we can be confident that
+          # only our python stuff is being captured in this cache (intentional).
+          path: ~/.cache
+          key: python-3.9-${{ hashFiles('poetry.lock') }}
+      - name: Setup Environment
+        uses: ./.github/actions/quality-stage
+      - name: Typecheck with pyright
+        run: poetry run pyright
+        shell: bash
+
   ruff-lint:
     runs-on: ubuntu-latest
     container: python:3.9

.gitlab-ci/.gitlab-test.yml

@@ -28,6 +28,7 @@ notebooks:
           "SimilarityScoring.ipynb",
           "SuperPixelSaliency.ipynb",
           "VIAME_OcclusionSaliency.ipynb",
+          "MC_RISE.ipynb",
           # # Shared memory issue on GitLab
           # "SerializedDetectionSaliency.ipynb",
           # Model comparison example is excluded due to computational complexity

docs/release_notes.rst

@@ -21,3 +21,4 @@ Release Notes
    release_notes/v0.9.2
    release_notes/v0.10.0
    release_notes/v0.11.0
+   release_notes/v0.12.0

docs/release_notes/v0.12.0.rst

@@ -0,0 +1,15 @@
+v0.12.0
+=======
+
+Bug fix for ``MC-RISE`` when threading is utilized, plus exemplar notebook demonstrating its use.
+
+Updates / New Features
+----------------------
+
+Examples
+
+* Added the ``MC-RISE`` example notebook that demonstrates the MC-RISE saliency
+  algorithm on a sample image from the GTSRB dataset.
+
+Fixes
+-----

pyproject.toml

@@ -26,7 +26,7 @@ classifiers = [
 # :auto package-meta:
 # package-specific meta, don't put this in "generated package-meta"
 authors = ["Kitware, Inc. <[email protected]>"]
-version = "0.11.0"
+version = "0.12.0"
 description = "Visual saliency map generation interfaces and baseline implementations for explainable AI."
 
 [tool.poetry.dependencies]
@@ -105,6 +105,7 @@ pre-commit = ">=2.20"
 ruff = "^0.5.6"
 types-setuptools = ">=65.6.0.1"
 sphinx-lint = ">=1.0.0"
+pyright = {version=">=1.1.320",extras=["nodejs"]}
 # :auto linting:
 
 # :auto docs:
@@ -245,3 +246,22 @@ incremental = false
 module = "tests.*"
 ignore_errors = true
 # :auto mypy:
+
+# :auto pyright:
+[tool.pyright]
+pythonVersion = "3.9"
+reportMissingImports = "warning"
+typeCheckingMode = "standard"
+include = [
+    "src/xaitk_saliency",
+    "tests",
+    "examples"
+    ]
+exclude = [
+    "**/__pycache__",
+    "demos",
+    "scripts",
+    "docs/_build",
+    "docs/_implementations",
+    ]
+# :auto pyright:

src/xaitk_saliency/impls/gen_image_classifier_blackbox_sal/mc_rise.py

@@ -73,7 +73,7 @@ def __init__(
         self._fill_colors = fill_colors
 
     @staticmethod
-    def _work_func(*, ref_image: np.ndarray, i_: int, m: np.ndarray, f: np.ndarray) -> np.ndarray:
+    def _work_func(ref_image: np.ndarray, i_: int, m: np.ndarray, f: np.ndarray) -> np.ndarray:
         s: tuple = (...,)
         if ref_image.ndim > 2:
             s = (..., None)  # add channel axis for multiplication
@@ -104,12 +104,15 @@ def _occlude_image_streaming(
             for i, (mask, fill) in enumerate(zip(masks, fill_values)):
                 yield MCRISEStack._work_func(ref_image=ref_image, i_=i, m=mask, f=fill)
         else:
+            ref_image = np.stack([ref_image for _ in fill_values], axis=0)
+            # NOTE: Never pass by keyword to avoid the iterables being wrongly
+            # zipped and assigned to kwargs.
             yield from parallel_map(
                 MCRISEStack._work_func,
-                ref_image=ref_image,
-                i_=itertools.count(),
-                m=masks,
-                f=fill_values,
+                ref_image,
+                itertools.count(),
+                masks,
+                fill_values,
                 cores=threads,
                 use_multiprocessing=False,
             )