From f6673faef3559b950f5bb8b2e2ee26f4ec91c630 Mon Sep 17 00:00:00 2001
From: Aaron Ponti <aaron@aaronponti.ch>
Date: Thu, 5 Feb 2026 15:14:28 +0100
Subject: [PATCH 1/2] Fix using a non-tuple sequence for multidimensional
 indexing that will result in error in pytorch 2.9.

---
 monai/inferers/utils.py | 25 +++++++++++++++++--------
 1 file changed, 17 insertions(+), 8 deletions(-)

diff --git a/monai/inferers/utils.py b/monai/inferers/utils.py
index 766486a807..5553cdcacf 100644
--- a/monai/inferers/utils.py
+++ b/monai/inferers/utils.py
@@ -223,14 +223,22 @@ def sliding_window_inference(
             for idx in slice_range
         ]
         if sw_batch_size > 1:
-            win_data = torch.cat([inputs[win_slice] for win_slice in unravel_slice]).to(sw_device)
+            win_data = torch.cat(
+                [inputs[tuple(win_slice) if isinstance(win_slice, list) else win_slice] for win_slice in unravel_slice]
+            ).to(sw_device)
             if condition is not None:
-                win_condition = torch.cat([condition[win_slice] for win_slice in unravel_slice]).to(sw_device)
+                win_condition = torch.cat(
+                    [condition[tuple(win_slice) if isinstance(win_slice, list) else win_slice] for win_slice in
+                     unravel_slice]
+                ).to(sw_device)
                 kwargs["condition"] = win_condition
         else:
-            win_data = inputs[unravel_slice[0]].to(sw_device)
+            s0 = unravel_slice[0]
+            s0_idx = tuple(s0) if isinstance(s0, list) else s0
+
+            win_data = inputs[s0_idx].to(sw_device)
             if condition is not None:
-                win_condition = condition[unravel_slice[0]].to(sw_device)
+                win_condition = condition[s0_idx].to(sw_device)
                 kwargs["condition"] = win_condition
 
         if with_coord:
@@ -257,7 +265,7 @@ def sliding_window_inference(
                 offset = s[buffer_dim + 2].start - c_start
                 s[buffer_dim + 2] = slice(offset, offset + roi_size[buffer_dim])
                 s[0] = slice(0, 1)
-                sw_device_buffer[0][s] += p * w_t
+                sw_device_buffer[0][tuple(s) if isinstance(s, list) else s] += p * w_t
             b_i += len(unravel_slice)
             if b_i < b_slices[b_s][0]:
                 continue
@@ -288,10 +296,11 @@ def sliding_window_inference(
                 o_slice[buffer_dim + 2] = slice(c_start, c_end)
                 img_b = b_s // n_per_batch  # image batch index
                 o_slice[0] = slice(img_b, img_b + 1)
+                o_slice_idx = tuple(o_slice) if isinstance(o_slice, list) else o_slice
                 if non_blocking:
-                    output_image_list[0][o_slice].copy_(sw_device_buffer[0], non_blocking=non_blocking)
+                    output_image_list[0][o_slice_idx].copy_(sw_device_buffer[0], non_blocking=non_blocking)
                 else:
-                    output_image_list[0][o_slice] += sw_device_buffer[0].to(device=device)
+                    output_image_list[0][o_slice_idx] += sw_device_buffer[0].to(device=device)
             else:
                 sw_device_buffer[ss] *= w_t
                 sw_device_buffer[ss] = sw_device_buffer[ss].to(device)
@@ -367,7 +376,7 @@ def _compute_coords(coords, z_scale, out, patch):
                 idx_zm[axis] = slice(
                     int(original_idx[axis].start * z_scale[axis - 2]), int(original_idx[axis].stop * z_scale[axis - 2])
                 )
-        out[idx_zm] += p
+        out[tuple(idx_zm)] += p
 
 
 def _get_scan_interval(

From 922dfff4db19ec733c4c48e8bd62ff6f387fed65 Mon Sep 17 00:00:00 2001
From: Aaron Ponti <aaron@aaronponti.ch>
Date: Thu, 5 Feb 2026 18:35:48 +0100
Subject: [PATCH 2/2] Fix formatting.

---
 monai/inferers/utils.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/monai/inferers/utils.py b/monai/inferers/utils.py
index 5553cdcacf..2ef754ddac 100644
--- a/monai/inferers/utils.py
+++ b/monai/inferers/utils.py
@@ -228,8 +228,10 @@ def sliding_window_inference(
             ).to(sw_device)
             if condition is not None:
                 win_condition = torch.cat(
-                    [condition[tuple(win_slice) if isinstance(win_slice, list) else win_slice] for win_slice in
-                     unravel_slice]
+                    [
+                        condition[tuple(win_slice) if isinstance(win_slice, list) else win_slice]
+                        for win_slice in unravel_slice
+                    ]
                 ).to(sw_device)
                 kwargs["condition"] = win_condition
         else: