TensorBoardCallback
CLASS - TensorBoardCallback(
- output_path:
str
- output_path:
Union[str, Path], None]
- update_interval:
int
= 50- ignored_keys:
Optional[set[str]]
= None- *args:
list
- **kwargs:
dict
)
Ancestors - (BaseCallback
)
Abstract base class used to build new callbacks. take as argument will contain keys for quantities relevant to the current batch or epoch (see method-specific docstrings).
Parameters:
- output_path (
str
) - output_path (
Union[str, Path], None]
) - update_interval (
int
) - ignored_keys (
Optional[set[str]]
)
Class Properties
Methods
- create_timestamp() ‑>
str
- get_distributed_global_rank(
kwargs: Optional[dict] = None
) ‑>Optional[int]
- get_distributed_local_rank(
kwargs: Optional[dict] = None
) ‑>Optional[int]
- get_distributed_world_size(
kwargs: Optional[dict] = None
) ‑>Optional[int]
- on_epoch_begin(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_epoch_end(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_evaluation_batch_begin(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- on_evaluation_batch_end(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- on_evaluation_begin(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_evaluation_end(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_train_batch_begin(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- on_train_batch_end(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- on_train_begin(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_train_end(
global_step: int, epoch: int, logs: dict, **kwargs: dict
) ‑>None
- on_warmup_batch_begin(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- on_warmup_batch_end(
global_step: int, epoch: int, step: int, logs: dict, **kwargs: dict
) ‑>None
- _internal_call_impl(
method_name: str, args: tuple, kwargs: dict
) ‑>None