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new a61e3ca0ab [Fix][ONNX] Fixed constant ROI handling in resize2d when
loading onnx models (#18138)
a61e3ca0ab is described below
commit a61e3ca0abde010c0696c515fa763b578e9e0fb9
Author: ConvolutedDog <[email protected]>
AuthorDate: Mon Jul 14 11:06:40 2025 +0800
[Fix][ONNX] Fixed constant ROI handling in resize2d when loading onnx
models (#18138)
* Fix onnx resize2d
* Fix onnx resize2d
* Fix onnx resize2d
* Add more roi cases for unittest
---
python/tvm/relax/frontend/onnx/onnx_frontend.py | 19 +++++++++-----
python/tvm/relax/op/image/image.py | 4 +++
tests/python/relax/test_frontend_onnx.py | 35 +++++++++++++++++++++++--
3 files changed, 49 insertions(+), 9 deletions(-)
diff --git a/python/tvm/relax/frontend/onnx/onnx_frontend.py
b/python/tvm/relax/frontend/onnx/onnx_frontend.py
index e3f6026fd6..5cf324086e 100644
--- a/python/tvm/relax/frontend/onnx/onnx_frontend.py
+++ b/python/tvm/relax/frontend/onnx/onnx_frontend.py
@@ -2126,13 +2126,18 @@ class Resize(OnnxOpConverter):
# Define relax implementation.
if roi is not None:
- roi = relax.op.concat(
- [
- relax.op.strided_slice(roi, axes=[0], begin=[2],
end=[ndims]),
- relax.op.strided_slice(roi, axes=[0], begin=[ndims + 2],
end=[2 * ndims]),
- ],
- axis=0,
- )
+ if isinstance(roi, relax.Constant):
+ roi = roi.data.numpy().tolist()
+ else:
+ roi = relax.op.concat(
+ [
+ relax.op.strided_slice(roi, axes=[0], begin=[2],
end=[ndims]),
+ relax.op.strided_slice(roi, axes=[0], begin=[ndims +
2], end=[2 * ndims]),
+ ],
+ axis=0,
+ )
+ # TODO The backend C++ func resize2d does not support dynamic
ROI for now.
+ raise NotImplementedError("Dynamic ROI is not supported in
resize2d for now.")
else:
roi = [0.0] * 4
diff --git a/python/tvm/relax/op/image/image.py
b/python/tvm/relax/op/image/image.py
index 6bec22161d..afadbf35fb 100644
--- a/python/tvm/relax/op/image/image.py
+++ b/python/tvm/relax/op/image/image.py
@@ -104,6 +104,10 @@ def resize2d(
roi = (0.0, 0.0, 0.0, 0.0) # type: ignore
elif isinstance(roi, float):
roi = (roi, roi, roi, roi) # type: ignore
+ elif isinstance(roi, (tuple, list)):
+ roi = tuple(val if isinstance(val, float) else float(val) for val in
roi)
+ else:
+ raise NotImplementedError(f"Unsupported roi type {type(roi)}")
if isinstance(size, (int, PrimExpr)):
size = (size, size)
diff --git a/tests/python/relax/test_frontend_onnx.py
b/tests/python/relax/test_frontend_onnx.py
index ece99d78f2..4afe7cd0aa 100644
--- a/tests/python/relax/test_frontend_onnx.py
+++ b/tests/python/relax/test_frontend_onnx.py
@@ -2359,8 +2359,34 @@ def test_tile(dynamic):
verify_tile(x.shape, repeats, z_array.shape)
-def test_resize():
- resize_node = helper.make_node("Resize", ["X", "", "scales"], ["Y"],
mode="cubic")
+def _generate_roi_cases():
+ # Base case when with_roi is False
+ roi_list = [
+ pytest.param(False, None, id="no_roi"),
+ ]
+
+ # Valid when with_roi is True
+ 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],
+ [0.2, 0.2, 0.8, 0.8],
+ [0.3, 0.3, 0.7, 0.7],
+ [0.4, 0.4, 0.6, 0.6],
+ [0.5, 0.5, 0.5, 0.5],
+ [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)}"))
+
+ return roi_list
+
+
[email protected]("with_roi, roi_list", _generate_roi_cases())
+def test_resize(with_roi, roi_list):
+ resize_node = helper.make_node(
+ "Resize", ["X", "roi" if with_roi else "", "scales"], ["Y"],
mode="cubic"
+ )
graph = helper.make_graph(
[resize_node],
@@ -2370,6 +2396,11 @@ def test_resize():
],
initializer=[
helper.make_tensor("scales", TensorProto.FLOAT, [4], [1.0, 1.0,
2.0, 2.0]),
+ *(
+ [helper.make_tensor("roi", TensorProto.FLOAT, [4], [0.0, 0.0,
0.0, 0.0])]
+ if with_roi
+ else []
+ ),
],
outputs=[
helper.make_tensor_value_info("Y", TensorProto.FLOAT, [1, 3, 64,
64]),
