Test to see if certain OSs are slow

.github/workflows/inference-test.yml

@@ -48,3 +48,28 @@ jobs:
       uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python }}
+
+  tests:
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        os: ["ubuntu-latest", "macos-13", "windows-latest"]
+    runs-on: ${{ matrix.os }}
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: "pip"
+          cache-dependency-path: "setup.py"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install torch --index-url https://download.pytorch.org/whl/cpu
+          pip install setuptools transformers pytest
+          pip install -e .
+      - name: Test with pytest
+        run: |
+          pytest test.py --durations=99

test.py

@@ -0,0 +1,23 @@
+import pytest
+import torch
+from transformers import AutoModelForCausalLM
+
+
+MODELS_TO_TEST = [
+    "hf-internal-testing/tiny-random-OPTForCausalLM",
+    "hf-internal-testing/tiny-random-GPT2LMHeadModel",
+    "hf-internal-testing/tiny-random-gpt_neo",
+]
+
+
+@pytest.mark.parametrize("model_id", MODELS_TO_TEST)
+@pytest.mark.parametrize("useless", [False, True])
+def test_inference(model_id, useless):
+    if useless:
+        # do nothing
+        pass
+
+    model = AutoModelForCausalLM.from_pretrained(model_id)
+    model.eval()
+    inputs = torch.tensor([[0, 1, 2, 3, 4]])
+    model.generate(inputs, do_sample=True, num_return_sequences=1)