test multiple ort

.github/workflows/ci.yml

@@ -36,6 +36,8 @@ jobs:
           - py311
           - py312
           - np1x
+          - ort117
+          - ort118
     steps:
       - name: Checkout branch
         uses: actions/checkout@v4

docs/intros/modelconversion.rst

@@ -110,3 +110,8 @@ We can use an ONNX backend like onnxruntime to run our model. Here we use onnxru
 
     print(out)
     # array([0, 0, 0, 1, 2, 2, 0, 1, 2, 1, 0, 2, 1, 1, 1, 2, 2, 0, 0, 1, 0, 1, 1, 0, 0, 2, 2, 2, 2, 2])
+
+.. note::
+
+    ONNX backends may not always support the entire ONNX specification and can sometimes miss kernel implementations for specific data types.
+    Since onnxruntime is such a common backend, ndonnx ensures proactively that any model generated using :func:`ndonnx.build` is compatible with at least the two latest onnxruntime releases on conda-forge.

ndonnx/_build.py

@@ -36,6 +36,8 @@ def build(
     -------
     out: onnx.ModelProto
         ONNX model
+
+    Note: the generated ONNX model should be runnable on the latest two versions of onnxruntime documented in an ndonnx release.
     """
 
     def collect_vars(name: str, arr: _CoreArray | Array):