This is an automated email from the ASF dual-hosted git repository.
tlopex pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
The following commit(s) were added to refs/heads/main by this push:
new 6be0db44c7 [Relax][Onnx][Resize] Fix ROI values when tensor ROI is
Empty pass node Constant (#18691)
6be0db44c7 is described below
commit 6be0db44c7a8cec44bb4583b994b73ad93693f6b
Author: Nguyen Duy Loc <[email protected]>
AuthorDate: Fri Jan 30 20:35:20 2026 +0700
[Relax][Onnx][Resize] Fix ROI values when tensor ROI is Empty pass node
Constant (#18691)
This PR fix ROI values when tensor ROI is Empty pass Constant node in
Resize Operator
### Description:
- Fix ROI values when tensor ROI is Empty pass Constant node
- Create test with Constant and Tensor ROI is Empty
### Step to Reproduce:
- Deploy yolov5n.onnx using TVM. When executing
relax.transform.LegalizeOps() is happen error: "IndexError: list index
out of range" at roi array, because roi = []
- Error log:
> "File ~/Contributes/tvm/python/tvm/topi/image/resize.py:615, in
_resize_2d()
> 608 in_x = x1 * (image_width - 1) + w_scale * x
> 609 else:
> 610 in_x = get_inx(
> 611 x,
> 612 image_width,
> 613 target_width,
> 614 coordinate_transformation_mode,
> --> 615 roi[1],
> 616 roi[3],
> 617 width_use_int_div,
> 618 )
> 619 in_y = get_inx(
> 620 y,
> 621 image_height,
> (...) 626 height_use_int_div,
> 627 )
> 629 if method == "nearest_neighbor":
> IndexError: list index out of range"
- Graph:
<img width="1000" height="500" alt="PR"
src="https://github.com/user-attachments/assets/e112511a-43a4-4555-afc6-e22d62ec095e";
/>
### Resolve:
- On the Frontend, when encountering a case where ROI is constant and
ROI is empty, the handling is the same as when ROI = None (fill in the
ROI tensor with 0.0).
---
python/tvm/relax/frontend/onnx/onnx_frontend.py | 4 ++-
tests/python/relax/test_frontend_onnx.py | 45 +++++++++++++++++++------
2 files changed, 38 insertions(+), 11 deletions(-)
diff --git a/python/tvm/relax/frontend/onnx/onnx_frontend.py
b/python/tvm/relax/frontend/onnx/onnx_frontend.py
index c71fd96caf..784be639dd 100644
--- a/python/tvm/relax/frontend/onnx/onnx_frontend.py
+++ b/python/tvm/relax/frontend/onnx/onnx_frontend.py
@@ -2277,6 +2277,8 @@ class Resize(OnnxOpConverter):
roi = roi.data.numpy().tolist()
if len(roi) == 2 * ndims:
roi = roi[2:ndims] + roi[ndims + 2 : 2 * ndims]
+ elif len(roi) == 0:
+ roi = [0.0] * (2 * (ndims - 2))
else:
roi = relax.op.concat(
[
@@ -2309,7 +2311,7 @@ class Resize(OnnxOpConverter):
elif isinstance(sizes, relax.expr.ShapeExpr):
sizes = [int(val.value) for val in sizes.values][2:]
else:
- assert f"Type {type(size)} for size is currently unsupported."
+ assert f"Type {type(sizes)} for size is currently unsupported."
if ndims == 3:
return bb.emit_te(
diff --git a/tests/python/relax/test_frontend_onnx.py
b/tests/python/relax/test_frontend_onnx.py
index b4b3baeb4d..62af660a31 100644
--- a/tests/python/relax/test_frontend_onnx.py
+++ b/tests/python/relax/test_frontend_onnx.py
@@ -2694,11 +2694,12 @@ def test_tile(dynamic):
def _generate_roi_cases():
# Base case when with_roi is False
roi_list = [
- pytest.param(False, None, id="no_roi"),
+ pytest.param(False, None, False, id="no_roi"),
]
- # Valid when with_roi is True
+ # Valid when with_roi is True and with_constant is True/False
roi_cases = [
+ [],
[0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 1.0],
[0.1, 0.1, 0.9, 0.9],
@@ -2709,27 +2710,51 @@ def _generate_roi_cases():
[0.1, 0.2, 0.9, 0.8],
]
for roi in roi_cases:
- roi_list.append(pytest.param(True, roi, id=f"roi_{'_'.join(str(x) for
x in roi)}"))
+ roi_list.append(pytest.param(True, roi, True,
id=f"roi_{'_'.join(str(x) for x in roi)}"))
+ roi_list.append(pytest.param(True, roi, False,
id=f"roi_{'_'.join(str(x) for x in roi)}"))
return roi_list
[email protected]("with_roi, roi_list", _generate_roi_cases())
-def test_resize(with_roi, roi_list):
[email protected]("with_roi, roi_list, with_constant",
_generate_roi_cases())
+def test_resize(with_roi, roi_list, with_constant):
+ nodes = []
resize_node = helper.make_node(
"Resize", ["X", "roi" if with_roi else "", "scales"], ["Y"],
mode="cubic"
)
+ if with_roi and with_constant:
+ roi_tensor = helper.make_tensor(
+ name="roi",
+ data_type=TensorProto.FLOAT,
+ dims=[len(roi_list)],
+ vals=roi_list,
+ )
+
+ roi_const_node = helper.make_node(
+ "Constant",
+ inputs=[],
+ outputs=["roi"],
+ value=roi_tensor,
+ )
+ nodes.append(roi_const_node)
+
+ nodes.append(resize_node)
+
+ initializers = [
+ helper.make_tensor("scales", TensorProto.FLOAT, [4], [1.0, 1.0, 2.0,
2.0]),
+ ]
+
+ if with_roi and not with_constant:
+ initializers.append(helper.make_tensor("roi", TensorProto.FLOAT,
[len(roi_list)], roi_list))
+
graph = helper.make_graph(
- [resize_node],
+ nodes,
"resize_test",
inputs=[
helper.make_tensor_value_info("X", TensorProto.FLOAT, [1, 3, 32,
32]),
],
- initializer=[
- helper.make_tensor("scales", TensorProto.FLOAT, [4], [1.0, 1.0,
2.0, 2.0]),
- *([helper.make_tensor("roi", TensorProto.FLOAT, [4], roi_list)] if
with_roi else []),
- ],
+ initializer=initializers,
outputs=[
helper.make_tensor_value_info("Y", TensorProto.FLOAT, [1, 3, 64,
64]),
],
