Bump onnxruntime to 1.16 | chore(ci) (#1070)

microsoft · Sep 21, 2023 · b6c5e3b · b6c5e3b
1 parent 64189f0
commit b6c5e3b
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diff --git a/docs/examples/02_plot_square_loss.py b/docs/examples/02_plot_square_loss.py
@@ -44,7 +44,7 @@ def square_loss(X: FLOAT["N", 1], Y: FLOAT["N", 1]) -> FLOAT[1, 1]:  # noqa: F82
 # And finally, we can use *onnxruntime* to compute the outputs
 # based on this model, using the standard onnxruntime API.
 
-sess = InferenceSession(model.SerializeToString())
+sess = InferenceSession(model.SerializeToString(), providers=("CPUExecutionProvider",))
 
 X = np.array([[0, 1, 2]], dtype=np.float32).T
 Y = np.array([[0.1, 1.2, 2.3]], dtype=np.float32).T

diff --git a/noxfile.py b/noxfile.py
@@ -27,7 +27,7 @@
     "pyyaml",
 )
 ONNX = "onnx==1.14.1"
-ONNX_RUNTIME = "onnxruntime==1.15.1"
+ONNX_RUNTIME = "onnxruntime==1.16.0"
 PYTORCH = "torch==2.0.1"
 ONNX_RUNTIME_NIGHTLY_DEPENDENCIES = (
     "flatbuffers",