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tensorboard

allennlp.training.callbacks.tensorboard

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TensorBoardCallback

@TrainerCallback.register("tensorboard")
class TensorBoardCallback(LogWriterCallback):
 | def __init__(
 |     self,
 |     serialization_dir: str,
 |     summary_interval: int = 100,
 |     distribution_interval: Optional[int] = None,
 |     batch_size_interval: Optional[int] = None,
 |     should_log_parameter_statistics: bool = False,
 |     should_log_learning_rate: bool = False
 | ) -> None

A callback that writes training statistics/metrics to TensorBoard.

log_scalars

class TensorBoardCallback(LogWriterCallback):
 | ...
 | def log_scalars(
 |     self,
 |     scalars: Dict[str, Union[int, float]],
 |     log_prefix: str = "",
 |     epoch: Optional[int] = None
 | ) -> None

log_tensors

class TensorBoardCallback(LogWriterCallback):
 | ...
 | def log_tensors(
 |     self,
 |     tensors: Dict[str, torch.Tensor],
 |     log_prefix: str = "",
 |     epoch: Optional[int] = None
 | ) -> None

close

class TensorBoardCallback(LogWriterCallback):
 | ...
 | def close(self) -> None

Calls the close method of the SummaryWriter s which makes sure that pending scalars are flushed to disk and the tensorboard event files are closed properly.