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# Ultralytics YOLO 🚀, AGPL-3.0 license
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from ultralytics.utils import LOGGER, TESTS_RUNNING, colorstr
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try:
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from torch.utils.tensorboard import SummaryWriter
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assert not TESTS_RUNNING # do not log pytest
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# TypeError for handling 'Descriptors cannot not be created directly.' protobuf errors in Windows
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except (ImportError, AssertionError, TypeError):
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SummaryWriter = None
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writer = None # TensorBoard SummaryWriter instance
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def _log_scalars(scalars, step=0):
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"""Logs scalar values to TensorBoard."""
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if writer:
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for k, v in scalars.items():
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writer.add_scalar(k, v, step)
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def on_pretrain_routine_start(trainer):
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"""Initialize TensorBoard logging with SummaryWriter."""
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if SummaryWriter:
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try:
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global writer
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writer = SummaryWriter(str(trainer.save_dir))
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prefix = colorstr('TensorBoard: ')
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LOGGER.info(f"{prefix}Start with 'tensorboard --logdir {trainer.save_dir}', view at http://localhost:6006/")
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except Exception as e:
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LOGGER.warning(f'WARNING ⚠️ TensorBoard not initialized correctly, not logging this run. {e}')
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def on_batch_end(trainer):
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"""Logs scalar statistics at the end of a training batch."""
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_log_scalars(trainer.label_loss_items(trainer.tloss, prefix='train'), trainer.epoch + 1)
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def on_fit_epoch_end(trainer):
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"""Logs epoch metrics at end of training epoch."""
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_log_scalars(trainer.metrics, trainer.epoch + 1)
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callbacks = {
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'on_pretrain_routine_start': on_pretrain_routine_start,
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'on_fit_epoch_end': on_fit_epoch_end,
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'on_batch_end': on_batch_end}
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