`ultralytics 8.2.94` Apple MPS train memory display (#16272)

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

.github/workflows/format.yml

@@ -38,12 +38,12 @@ jobs:
 
             Join the Ultralytics community where it suits you best. For real-time chat, head to [Discord](https://ultralytics.com/discord) 🎧. Prefer in-depth discussions? Check out [Discourse](https://community.ultralytics.com). Or dive into threads on our [Subreddit](https://reddit.com/r/ultralytics) to share knowledge with the community.
 
-            ## Install
+            ## Upgrade
 
-            Pip install the `ultralytics` package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/).
+            Upgrade to the latest `ultralytics` package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/) to verify your issue is not already resolved in the latest version:
 
             ```bash
-            pip install ultralytics
+            pip install -U ultralytics
             ```
 
             ## Environments

.github/workflows/publish.yml

@@ -85,6 +85,12 @@ jobs:
           if publish:
               print('Ready to publish new version to PyPI ✅.')
         id: check_pypi
+      - name: Publish to PyPI
+        continue-on-error: true
+        if: (github.event_name == 'push' || github.event.inputs.pypi == 'true')  && steps.check_pypi.outputs.increment == 'True'
+        run: |
+          python -m build
+          python -m twine upload dist/* -u __token__ -p ${{ secrets.PYPI_TOKEN }}
       - name: Publish new tag
         if: (github.event_name == 'push' || github.event.inputs.pypi == 'true')  && steps.check_pypi.outputs.increment == 'True'
         run: |
@@ -100,14 +106,6 @@ jobs:
         run: |
           curl -s "https://raw.githubusercontent.com/ultralytics/actions/main/utils/summarize_release.py" | python -
         shell: bash
-      - name: Publish to PyPI
-        continue-on-error: true
-        if: (github.event_name == 'push' || github.event.inputs.pypi == 'true')  && steps.check_pypi.outputs.increment == 'True'
-        env:
-          PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}
-        run: |
-          python -m build
-          python -m twine upload dist/* -u __token__ -p $PYPI_TOKEN
       - name: Extract PR Details
         env:
           GH_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN || secrets.GITHUB_TOKEN }}

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.2.93"
+__version__ = "8.2.94"
 
 
 import os

ultralytics/engine/trainer.py

@@ -28,7 +28,6 @@ from ultralytics.utils import (
     DEFAULT_CFG,
     LOCAL_RANK,
     LOGGER,
-    MACOS,
     RANK,
     TQDM,
     __version__,
@@ -409,13 +408,17 @@ class BaseTrainer:
                             break
 
                 # Log
-                mem = f"{torch.cuda.memory_reserved() / 1E9 if torch.cuda.is_available() else 0:.3g}G"  # (GB)
-                loss_len = self.tloss.shape[0] if len(self.tloss.shape) else 1
-                losses = self.tloss if loss_len > 1 else torch.unsqueeze(self.tloss, 0)
                 if RANK in {-1, 0}:
+                    loss_length = self.tloss.shape[0] if len(self.tloss.shape) else 1
                     pbar.set_description(
-                        ("%11s" * 2 + "%11.4g" * (2 + loss_len))
+                        ("%11s" * 2 + "%11.4g" * (2 + loss_length))
-                        % (f"{epoch + 1}/{self.epochs}", mem, *losses, batch["cls"].shape[0], batch["img"].shape[-1])
+                        % (
+                            f"{epoch + 1}/{self.epochs}",
+                            f"{self._get_memory():.3g}G",  # (GB) GPU memory util
+                            *(self.tloss if loss_length > 1 else torch.unsqueeze(self.tloss, 0)),  # losses
+                            batch["cls"].shape[0],  # batch size, i.e. 8
+                            batch["img"].shape[-1],  # imgsz, i.e 640
+                        )
                     )
                     self.run_callbacks("on_batch_end")
                     if self.args.plots and ni in self.plot_idx:
@@ -453,11 +456,7 @@ class BaseTrainer:
                 self.scheduler.last_epoch = self.epoch  # do not move
                 self.stop |= epoch >= self.epochs  # stop if exceeded epochs
             self.run_callbacks("on_fit_epoch_end")
-            gc.collect()
+            self._clear_memory()
-            if MACOS and self.device.type == "mps":
-                torch.mps.empty_cache()  # clear unified memory at end of epoch, may help MPS' management of 'unlimited' virtual memoy
-            else:
-                torch.cuda.empty_cache()  # clear GPU memory at end of epoch, may help reduce CUDA out of memory errors
 
             # Early Stopping
             if RANK != -1:  # if DDP training
@@ -478,14 +477,29 @@ class BaseTrainer:
             if self.args.plots:
                 self.plot_metrics()
             self.run_callbacks("on_train_end")
+        self._clear_memory()
+        self.run_callbacks("teardown")
+
+    def _get_memory(self):
+        """Get accelerator memory utilization in GB."""
+        if self.device.type == "mps":
+            memory = torch.mps.driver_allocated_memory()
+        elif self.device.type == "cpu":
+            memory = 0
+        else:
+            memory = torch.cuda.memory_reserved()
+        return memory / 1e9
+
+    def _clear_memory(self):
+        """Clear accelerator memory on different platforms."""
         gc.collect()
-        if MACOS and self.device.type == "mps":
+        if self.device.type == "mps":
             torch.mps.empty_cache()
+        elif self.device.type == "cpu":
+            return
         else:
             torch.cuda.empty_cache()
 
-        self.run_callbacks("teardown")
-
     def read_results_csv(self):
         """Read results.csv into a dict using pandas."""
         import pandas as pd  # scope for faster 'import ultralytics'