From d9d49b9518c3d67b50fbb94f8c10d81bded96892 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Wed, 11 Mar 2026 16:28:24 +0000
Subject: [PATCH 1/2] Initial plan


From 0bebad41c8470db0e904a207366e09d9a793a5e8 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Wed, 11 Mar 2026 16:33:34 +0000
Subject: [PATCH 2/2] Fix cubic_coeff_a=-0.5 for bicubic antialias=True in
 torchlib

Co-authored-by: justinchuby <11205048+justinchuby@users.noreply.github.com>
---
 onnxscript/function_libs/torch_lib/ops/nn.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/onnxscript/function_libs/torch_lib/ops/nn.py b/onnxscript/function_libs/torch_lib/ops/nn.py
index ee6f589851..de89ff6bad 100644
--- a/onnxscript/function_libs/torch_lib/ops/nn.py
+++ b/onnxscript/function_libs/torch_lib/ops/nn.py
@@ -2329,6 +2329,7 @@ def _aten_upsample_output_size(
     mode: str,
     coordinate_transformation_mode: str,
     antialias: int = 0,
+    cubic_coeff_a: float = -0.75,
 ) -> TReal:
     batch_and_channel = op.Shape(self, end=2, start=0)
     # When output_size is passed in as a list of integers, the torch.onnx
@@ -2344,6 +2345,7 @@ def _aten_upsample_output_size(
         output_size,
         mode=mode,
         coordinate_transformation_mode=coordinate_transformation_mode,
+        cubic_coeff_a=cubic_coeff_a,
         nearest_mode="floor",
         antialias=antialias,
     )
@@ -2355,6 +2357,7 @@ def _aten_upsample_scales(
     mode: str,
     coordinate_transformation_mode: str,
     antialias: int = 0,
+    cubic_coeff_a: float = -0.75,
 ) -> TReal:
     return op.Resize(
         self,
@@ -2365,6 +2368,7 @@ def _aten_upsample_scales(
         None,
         mode=mode,
         coordinate_transformation_mode=coordinate_transformation_mode,
+        cubic_coeff_a=cubic_coeff_a,
         nearest_mode="floor",
         antialias=antialias,
     )
@@ -2404,12 +2408,15 @@ def aten__upsample_bicubic2d_aa(
     # NOTE: Based on experimentation, scales_h and scales_w are always ignored in PyTorch,
     # unless when align_corners is True, in which case we do not know what is going on.
     coordinate_transformation_mode = _get_upsample_align_corners_mode(align_corners)
+    # PyTorch uses cubic_coeff_a=-0.5 (Keys interpolation, PIL-compatible) when
+    # antialias=True, as opposed to -0.75 (OpenCV-compatible) for the non-antialias case.
     return _aten_upsample_output_size(
         self,
         output_size,
         mode="cubic",
         coordinate_transformation_mode=coordinate_transformation_mode,
         antialias=1,
+        cubic_coeff_a=-0.5,
     )