o W h @sddlmZmZmZmZmZz(erJeddusJdaedZddlZddl m Z ddl Z ddl m Z WneeeefyEdZ Ynwdded ed dfd d Zdd dZdddZdddZdddZdddZe rveeeedZdSiZdS))LOGGERSETTINGS TESTS_RUNNINGcolorstr torch_utils tensorboardTNz TensorBoard: )deepcopy) SummaryWriterscalarsstepreturncCs,tr|D] \}}t|||qdSdS)a Log scalar values to TensorBoard. Args: scalars (dict): Dictionary of scalar values to log to TensorBoard. Keys are scalar names and values are the corresponding scalar values. step (int): Global step value to record with the scalar values. Used for x-axis in TensorBoard graphs. Examples: >>> # Log training metrics >>> metrics = {"loss": 0.5, "accuracy": 0.95} >>> _log_scalars(metrics, step=100) N)WRITERitems add_scalar)r r kvr[/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/utils/callbacks/tensorboard.py _log_scalarss rcCs|jj}t|tr ||fn|}t|j}tjddg|R|j |j d}t t j dtdt j dtjjdz'|jttjjt|j|ddgttdWWd d Styz?tt|j}||jdd }|D] }t|d rd |_d |_ q||ttjj||ddgttdWnty}zt!td|WYd }~nd }~wwYnwWd d S1swYd S)aJ Log model graph to TensorBoard. This function attempts to visualize the model architecture in TensorBoard by tracing the model with a dummy input tensor. It first tries a simple method suitable for YOLO models, and if that fails, falls back to a more complex approach for models like RTDETR that may require special handling. Args: trainer (BaseTrainer): The trainer object containing the model to visualize. Must have attributes: - model: PyTorch model to visualize - args: Configuration arguments with 'imgsz' attribute Notes: This function requires TensorBoard integration to be enabled and the global WRITER to be initialized. It handles potential warnings from the PyTorch JIT tracer and attempts to gracefully handle different model architectures. )devicedtypeignore)categoryF)strictu#model graph visualization added ✅N)verboseexportT torchscriptz(TensorBoard graph visualization failure )"argsimgsz isinstanceintnextmodel parameterstorchzerosrrwarningscatch_warnings simplefilter UserWarningjit TracerWarningevalr add_graphtracer de_parallelrinfoPREFIX Exceptionrfusemoduleshasattrrformatwarning)trainerr pimr$merrr_log_tensorboard_graph+sD  "     "r?c Csptr6ztt|jattd|jdWdSty5}zttd|WYd}~dSd}~wwdS)z2Initialize TensorBoard logging with SummaryWriter.z!Start with 'tensorboard --logdir z!', view at http://localhost:6006/z=TensorBoard not initialized correctly, not logging this run. N) r strsave_dirr rr2r3r4r9)r:r>rrron_pretrain_routine_start_s"rBcCstrt|dSdS)zLog TensorBoard graph.N)r r?r:rrron_train_startjs rDcCs2t|j|jdd|jdt|j|jddS)z6Logs scalar statistics at the end of a training epoch.train)prefixrN)rlabel_loss_itemstlossepochlrrCrrron_train_epoch_endpsrKcCst|j|jddS)z,Logs epoch metrics at end of training epoch.rN)rmetricsrIrCrrron_fit_epoch_endvsrM)rBrDrMrK)r)r N)ultralytics.utilsrrrrrr r3r(copyrr&torch.utils.tensorboardr ImportErrorAssertionError TypeErrorAttributeErrordictr"rr?rBrDrKrM callbacksrrrrs:   4