guan404ming commented on code in PR #19863:
URL: https://github.com/apache/tvm/pull/19863#discussion_r3451598255
##########
tests/python/relax/test_frontend_onnx.py:
##########
@@ -5579,6 +5579,32 @@ def test_affine_grid(align_corners):
check_correctness(model, opset=20)
+def test_affine_grid_3d():
+ affine_grid_node = helper.make_node(
+ "AffineGrid",
+ ["theta", "size"],
+ ["grid"],
+ align_corners=1,
+ )
+
+ graph = helper.make_graph(
+ [affine_grid_node],
+ "affine_grid_3d_test",
+ inputs=[
+ helper.make_tensor_value_info("theta", TensorProto.FLOAT, [2, 3,
4]),
+ ],
+ initializer=[
+ helper.make_tensor("size", TensorProto.INT64, [5], [2, 3, 8, 16,
16]),
+ ],
+ outputs=[
+ helper.make_tensor_value_info("grid", TensorProto.FLOAT, [2, 8,
16, 16, 3]),
+ ],
+ )
+
+ model = helper.make_model(graph, producer_name="affine_grid_3d_test")
+ check_correctness(model, opset=20)
Review Comment:
Make sense to me, thanks for letting me know. Just switched
`test_affine_grid_3d` to a structural verify, no more onnxruntime execution,
just imports and asserts on the IR (affine_grid + permute_dims and output
shape).
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