回传数据解析，兼容v5和v10

ultralytics/utils/callbacks/tensorboard.py

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+# Ultralytics YOLO 🚀, AGPL-3.0 license
+import contextlib
+
+from ultralytics.utils import LOGGER, SETTINGS, TESTS_RUNNING, colorstr
+
+try:
+    # WARNING: do not move SummaryWriter import due to protobuf bug https://github.com/ultralytics/ultralytics/pull/4674
+    from torch.utils.tensorboard import SummaryWriter
+
+    assert not TESTS_RUNNING  # do not log pytest
+    assert SETTINGS["tensorboard"] is True  # verify integration is enabled
+    WRITER = None  # TensorBoard SummaryWriter instance
+    PREFIX = colorstr("TensorBoard: ")
+
+    # Imports below only required if TensorBoard enabled
+    import warnings
+    from copy import deepcopy
+    from ultralytics.utils.torch_utils import de_parallel, torch
+
+except (ImportError, AssertionError, TypeError, AttributeError):
+    # TypeError for handling 'Descriptors cannot not be created directly.' protobuf errors in Windows
+    # AttributeError: module 'tensorflow' has no attribute 'io' if 'tensorflow' not installed
+    SummaryWriter = None
+
+
+def _log_scalars(scalars, step=0):
+    """Logs scalar values to TensorBoard."""
+    if WRITER:
+        for k, v in scalars.items():
+            WRITER.add_scalar(k, v, step)
+
+
+def _log_tensorboard_graph(trainer):
+    """Log model graph to TensorBoard."""
+
+    # Input image
+    imgsz = trainer.args.imgsz
+    imgsz = (imgsz, imgsz) if isinstance(imgsz, int) else imgsz
+    p = next(trainer.model.parameters())  # for device, type
+    im = torch.zeros((1, 3, *imgsz), device=p.device, dtype=p.dtype)  # input image (must be zeros, not empty)
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", category=UserWarning)  # suppress jit trace warning
+        warnings.simplefilter("ignore", category=torch.jit.TracerWarning)  # suppress jit trace warning
+
+        # Try simple method first (YOLO)
+        with contextlib.suppress(Exception):
+            trainer.model.eval()  # place in .eval() mode to avoid BatchNorm statistics changes
+            WRITER.add_graph(torch.jit.trace(de_parallel(trainer.model), im, strict=False), [])
+            LOGGER.info(f"{PREFIX}model graph visualization added ✅")
+            return
+
+        # Fallback to TorchScript export steps (RTDETR)
+        try:
+            model = deepcopy(de_parallel(trainer.model))
+            model.eval()
+            model = model.fuse(verbose=False)
+            for m in model.modules():
+                if hasattr(m, "export"):  # Detect, RTDETRDecoder (Segment and Pose use Detect base class)
+                    m.export = True
+                    m.format = "torchscript"
+            model(im)  # dry run
+            WRITER.add_graph(torch.jit.trace(model, im, strict=False), [])
+            LOGGER.info(f"{PREFIX}model graph visualization added ✅")
+        except Exception as e:
+            LOGGER.warning(f"{PREFIX}WARNING ⚠️ TensorBoard graph visualization failure {e}")
+
+
+def on_pretrain_routine_start(trainer):
+    """Initialize TensorBoard logging with SummaryWriter."""
+    if SummaryWriter:
+        try:
+            global WRITER
+            WRITER = SummaryWriter(str(trainer.save_dir))
+            LOGGER.info(f"{PREFIX}Start with 'tensorboard --logdir {trainer.save_dir}', view at http://localhost:6006/")
+        except Exception as e:
+            LOGGER.warning(f"{PREFIX}WARNING ⚠️ TensorBoard not initialized correctly, not logging this run. {e}")
+
+
+def on_train_start(trainer):
+    """Log TensorBoard graph."""
+    if WRITER:
+        _log_tensorboard_graph(trainer)
+
+
+def on_train_epoch_end(trainer):
+    """Logs scalar statistics at the end of a training epoch."""
+    _log_scalars(trainer.label_loss_items(trainer.tloss, prefix="train"), trainer.epoch + 1)
+    _log_scalars(trainer.lr, trainer.epoch + 1)
+
+
+def on_fit_epoch_end(trainer):
+    """Logs epoch metrics at end of training epoch."""
+    _log_scalars(trainer.metrics, trainer.epoch + 1)
+
+
+callbacks = (
+    {
+        "on_pretrain_routine_start": on_pretrain_routine_start,
+        "on_train_start": on_train_start,
+        "on_fit_epoch_end": on_fit_epoch_end,
+        "on_train_epoch_end": on_train_epoch_end,
+    }
+    if SummaryWriter
+    else {}
+)