netket.logging.TensorBoardLog

class netket.logging.TensorBoardLog

Bases: AbstractLog

Creates a tensorboard logger using tensorboardX’s summarywriter.

Refer to its documentation for further details

https://tensorboardx.readthedocs.io/en/latest/tensorboard.html

TensorBoardX must be installed.

Parameters:

• logdir (string) – Save directory location. Default is runs/CURRENT_DATETIME_HOSTNAME, which changes after each run. Use hierarchical folder structure to compare between runs easily. e.g. pass in ‘runs/exp1’, ‘runs/exp2’, etc. for each new experiment to compare across them.

• comment (string) – Comment logdir suffix appended to the default logdir. If logdir is assigned, this argument has no effect.

• purge_step (int) – When logging crashes at step \(T+X\) and restarts at step \(T\), any events whose global_step larger or equal to \(T\) will be purged and hidden from TensorBoard. Note that crashed and resumed experiments should have the same logdir.

• max_queue (int) – Size of the queue for pending events and summaries before one of the ‘add’ calls forces a flush to disk. Default is ten items.

• flush_secs (int) – How often, in seconds, to flush the pending events and summaries to disk. Default is every two minutes.

• filename_suffix (string) – Suffix added to all event filenames in the logdir directory. More details on filename construction in tensorboard.summary.writer.event_file_writer.EventFileWriter.

• write_to_disk (boolean) – If pass False, TensorBoardLog will not write to disk.

Examples

Logging optimisation to tensorboard.

>>> import pytest; pytest.skip("skip automated test of this docstring")
>>>
>>> import netket as nk
>>> # create a summary writer with automatically generated folder name.
>>> writer = nk.logging.TensorBoardLog()
>>> # folder location: runs/May04_22-14-54_s-MacBook-Pro.local/
>>> # create a summary writer using the specified folder name.
>>> writer = nk.logging.TensorBoardLog("my_experiment")
>>> # folder location: my_experiment
>>> # create a summary writer with comment appended.
>>> writer = nk.logging.TensorBoardLog(comment="LR_0.1_BATCH_16")
>>> # folder location: runs/May04_22-14-54_s-MacBook-Pro.localLR_0.1_BATCH_16/

Inheritance

Methods

__call__(step, item, variational_state=None)

Logs at a given integer step a dictionary of data, optionally specifying a variational state to encode additional data.

Parameters:

• step (int) – monotonically increasing integer representing the row in the database corresponding to this log entry;

• item (dict[str, Any]) – Any dictionary of data to be logged;

• variational_state (VariationalState | None) – optional variational state from which additional data might be extracted.

flush(variational_state=None)

Writes to file the content of this logger.

Parameters:

machine – optionally also writes the parameters of the machine.