Added gitlab pipeline trigger

.github/workflows/gpu_ci_trigger.yml

@@ -0,0 +1,49 @@
+name: Sync to GitLab and Run GPU CI
+
+on:
+  push:
+    branches: [main, devel]
+  pull_request:
+    branches: [main, devel]
+  workflow_dispatch:
+
+jobs:
+  sync-and-test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Install SSH Key
+        uses: webfactory/ssh-agent@v0.9.0
+        with:
+          ssh-private-key: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
+
+      - name: Push to GitLab via SSH & Provide Link
+        run: |
+          # 1. Setup SSH known hosts
+          mkdir -p ~/.ssh
+          ssh-keyscan gitlab.mpcdf.mpg.de >> ~/.ssh/known_hosts
+
+          # 2. Determine target branch
+          if [ "${{ github.event_name }}" == "pull_request" ]; then
+            TARGET_BRANCH="pr-${{ github.event.number }}"
+          else
+            TARGET_BRANCH="${{ github.ref_name }}"
+          fi
+
+          # 3. Add GitLab SSH remote
+          git remote add gitlab git@gitlab.mpcdf.mpg.de:maxlin/cunumpy.git
+
+          # 4. Force push (This automatically starts the GitLab Pipeline)
+          git push -f gitlab HEAD:refs/heads/$TARGET_BRANCH
+
+          # 5. Provide the direct link
+          # We construct the URL manually since the push triggers the pipeline automatically
+          PIPELINE_URL="https://gitlab.mpcdf.mpg.de/maxlin/cunumpy/-/pipelines?ref=$TARGET_BRANCH"
+
+          echo "::notice::GitLab GPU CI Pipeline started automatically via Push!"
+          echo "::notice::View Pipeline: $PIPELINE_URL"
+

.gitlab-ci.yml

@@ -1,57 +1,40 @@
-# This file is a template, and might need editing before it works on your project.
-# To contribute improvements to CI/CD templates, please follow the Development guide at:
-# https://docs.gitlab.com/ee/development/cicd/templates.html
-# This specific template is located at:
-# https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Python.gitlab-ci.yml
-
-# Official language image. Look for the different tagged releases at:
-# https://hub.docker.com/r/library/python/tags/
-image: python:latest
-
-# Change pip's cache directory to be inside the project directory since we can
-# only cache local items.
 variables:
-  PIP_CACHE_DIR: "$CI_PROJECT_DIR/.cache/pip"
-
-# https://pip.pypa.io/en/stable/topics/caching/
-cache:
-  paths:
-    - .cache/pip
-
-before_script:
-  - python --version ; pip --version  # For debugging
-  - pip install virtualenv
-  - virtualenv venv
-  - source venv/bin/activate
-
-test:
+  # Use the specialized MPCDF HPC image
+  CUDA_IMAGE: "gitlab-registry.mpcdf.mpg.de/mpcdf/ci-module-image/nvhpcsdk_26:2026"
+  PIP_DISABLE_PIP_VERSION_CHECK: "1"
+
+stages:
+  - test
+
+gpu_tests:
+  stage: test
+  image: ${CUDA_IMAGE}
+  tags:
+    - gpu-nvidia
+    - gpu-nvidia-cc80
+  before_script:
+    - module load python-waterboa/2025.06
+    - module load nvhpcsdk/26
   script:
-    - pip install ruff tox  # you can also use tox
-    - pip install --editable ".[test]"
-    - tox -e py,ruff
-
-run:
-  script:
-    - pip install .
-    # run the command here
-  artifacts:
-    paths:
-      - build/*
-
-pages:
-  script:
-    - pip install sphinx sphinx-rtd-theme
-    - cd doc
-    - make html
-    - mv build/html/ ../public/
-  artifacts:
-    paths:
-      - public
-  rules:
-    - if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
-
-deploy:
-  stage: deploy
-  script: echo "Define your deployment script!"
-  environment: production
-
+    - echo "--- CUDA Sanity Check ---"
+    - nvidia-smi
+
+    - echo "--- Detect Compute Capability ---"
+    - nvidia-smi --query-gpu=compute_cap --format=csv,noheader
+
+    - echo "--- Tool Versions ---"
+    - cmake --version
+    - python3 --version
+    - git --version
+
+    - echo "--- Pytest Execution ---"
+    # The MPCDF image likely has a specific python environment. 
+    # We install our dependencies into the user directory or a virtualenv.
+    - python3 -m pip install --user cupy-cuda12x
+    - python3 -m pip install --user -e .
+
+    # Add the user bin to PATH for pytest
+    - export PATH="$HOME/.local/bin:$PATH"
+    - export ARRAY_BACKEND=cupy
+
+    - python3 -m pytest tests/unit/

CHANGELOG.md

@@ -22,6 +22,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
     - `xp.synchronize()`: Blocks until GPU operations are complete (no-op on CPU). Essential for accurate benchmarking.
 - **Developer Experience**:
     - Added `isort` configuration to `pyproject.toml` with `black` profile compatibility.
+    - Reorganized test suite into specialized files: `test_numpy.py`, `test_cupy.py`, and `test_cunumpy.py`.
 
 ### Changed
 - **Dynamic Dispatch Architecture**: Refactored `src/cunumpy/xp.py` to use module-level `__getattr__`. This ensures that `cunumpy.<op>` calls always resolve to the currently active backend module, enabling seamless runtime switching via `set_backend`.

tests/unit/test_cunumpy.py

@@ -0,0 +1,58 @@
+import numpy as np
+import pytest
+
+import cunumpy as xp
+
+
+def test_to_numpy():
+    arr = xp.array([1, 2, 3])
+    # Even if it's already numpy, to_numpy should work
+    arr_np = xp.to_numpy(arr)
+    assert isinstance(arr_np, np.ndarray)
+    assert np.array_equal(arr_np, [1, 2, 3])
+
+
+def test_to_cunumpy():
+    arr = np.array([1, 2, 3])
+    arr_xp = xp.to_cunumpy(arr)
+    # Backend is numpy in tests usually
+    assert isinstance(arr_xp, (np.ndarray, xp.ndarray))
+
+
+def test_get_backend_and_is_gpu_cpu():
+    arr = np.array([1, 2, 3])
+    assert xp.get_backend(arr) == "numpy"
+    assert xp.is_gpu(arr) is False
+    assert xp.is_cpu(arr) is True
+
+
+def test_use_backend():
+    # Initial backend should be numpy (default) in this test environment
+    assert "numpy" in xp.xp.__name__
+
+    with xp.use_backend("numpy"):
+        assert "numpy" in xp.xp.__name__
+        arr = xp.zeros(10)
+        assert isinstance(arr, np.ndarray)
+
+    assert "numpy" in xp.xp.__name__
+
+
+def test_set_backend():
+    # Set to numpy
+    xp.set_backend("numpy")
+    assert "numpy" in xp.xp.__name__
+    arr = xp.array([1])
+    assert isinstance(arr, np.ndarray)
+
+    # Set to cupy (falls back to numpy if not available)
+    xp.set_backend("cupy")
+    # If cupy is not installed, xp.xp will be numpy module
+    arr2 = xp.array([2])
+    assert arr2 is not None
+
+
+def test_backend_bools():
+    with xp.use_backend("numpy"):
+        assert xp.numpy_backend is True
+        assert xp.cupy_backend is False

tests/unit/test_cupy.py

@@ -0,0 +1,54 @@
+import numpy as np
+import pytest
+
+import cunumpy as xp
+
+
+def test_to_cupy_available():
+    try:
+        import cupy as cp
+    except ImportError:
+        pytest.skip("CuPy not installed")
+
+    with xp.use_backend("cupy"):
+        arr = np.array([1, 2, 3])
+        arr_cp = xp.to_cupy(arr)
+        assert isinstance(arr_cp, cp.ndarray)
+
+
+def test_to_cupy_not_available():
+    try:
+        import cupy
+
+        pytest.skip("CuPy is installed, cannot test missing cupy error")
+    except ImportError:
+        pass
+
+    with xp.use_backend("cupy"):
+        arr = np.array([1, 2, 3])
+        with pytest.raises(ImportError):
+            xp.to_cupy(arr)
+
+
+def test_synchronize():
+    # Should not crash on any backend
+    xp.synchronize()
+
+    with xp.use_backend("numpy"):
+        xp.synchronize()
+
+    with xp.use_backend("cupy"):
+        xp.synchronize()
+
+
+def test_xp_array_cupy():
+    try:
+        import cupy as cp
+    except ImportError:
+        pytest.skip("CuPy not installed")
+
+    with xp.use_backend("cupy"):
+        arr = xp.array([1, 2])
+        arr *= 2
+        assert isinstance(arr, cp.ndarray)
+        assert cp.asnumpy(arr).tolist() == [2, 4]