`ultralytics 8.2.79` YOLOv10 CoreML and MPS training "gather" op error fix (#15672)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.2.78"
+__version__ = "8.2.79"
 
 import os
 

ultralytics/nn/modules/head.py

@@ -8,6 +8,7 @@ import torch
 import torch.nn as nn
 from torch.nn.init import constant_, xavier_uniform_
 
+from ultralytics.utils import MACOS
 from ultralytics.utils.tal import TORCH_1_10, dist2bbox, dist2rbox, make_anchors
 
 from .block import DFL, BNContrastiveHead, ContrastiveHead, Proto
@@ -151,13 +152,16 @@ class Detect(nn.Module):
         boxes = torch.gather(boxes, dim=1, index=index.repeat(1, 1, boxes.shape[-1]))
         scores = torch.gather(scores, dim=1, index=index.repeat(1, 1, scores.shape[-1]))
 
-        # NOTE: simplify but result slightly lower mAP
+        # NOTE: simplify result but slightly lower mAP
         # scores, labels = scores.max(dim=-1)
         # return torch.cat([boxes, scores.unsqueeze(-1), labels.unsqueeze(-1)], dim=-1)
 
         scores, index = torch.topk(scores.flatten(1), max_det, axis=-1)
         labels = index % nc
         index = index // nc
+        # Set int64 dtype for MPS and CoreML compatibility to avoid 'gather_along_axis' ops error
+        if MACOS:
+            index = index.to(torch.int64)
         boxes = boxes.gather(dim=1, index=index.unsqueeze(-1).repeat(1, 1, boxes.shape[-1]))
 
         return torch.cat([boxes, scores.unsqueeze(-1), labels.unsqueeze(-1).to(boxes.dtype)], dim=-1)