mm.training.callbacks.TensorboardCallback

class mrmustard.training.callbacks.TensorboardCallback(tag=None, steps_per_call=1, root_logdir='./tb_logdir', experiment_tag=None, prefix=None, cost_converter=None, track_grads=False, log_objectives=True, log_trainables=False)

Bases: Callback

Callback for enabling Tensorboard tracking of optimization progresses.

Things tracked:

• the cost

• the transformed cost, if a cost_converter is provided

• trainable parameter values

• trainable parameter gradients (if track_grads is True)

To start the Tensorboard frontend, either:

• use VSCode: F1 -> Tensorboard -> select your root_logdir/experiment_tag.

• use command line: tensorboard –logdir=root_logdir/experiment_tag and open link in browser.

Attributes

cost_converter	Transformation on cost for the purpose of better interpretation.
experiment_tag	The tag for experiment subfolder to group similar optimizations together for easy comparisons.
log_objectives	Whether to return objectives in the callback results to be stored.
log_trainables	Whether to return parameter values in the callback results to be stored.
prefix	Extra prefix to name the optimization experiment.
root_logdir	The root logdir for tensorboard logging.
steps_per_call	Sets calling frequency of this callback.
tag	Custom tag for a callback instance to be used as keys in Optimizer.callback_history.
track_grads	Whether to track gradients as well as the values for trainable parameters.

cost_converter: Optional[Callable] = None

Transformation on cost for the purpose of better interpretation.

experiment_tag: Optional[str] = None

The tag for experiment subfolder to group similar optimizations together for easy comparisons. Defaults to the hash of all trainable variables’ names.

log_objectives: bool = True

Whether to return objectives in the callback results to be stored.

log_trainables: bool = False

Whether to return parameter values in the callback results to be stored.

prefix: Optional[str] = None

Extra prefix to name the optimization experiment.

root_logdir: Union[str, Path] = './tb_logdir'

The root logdir for tensorboard logging.

steps_per_call: int = 1

Sets calling frequency of this callback. Defaults to once per optimization step. Use higher values to reduce overhead.

tag: str = None

Custom tag for a callback instance to be used as keys in Optimizer.callback_history. Defaults to the class name.

track_grads: bool = False

Whether to track gradients as well as the values for trainable parameters.

Methods

__call__(**kwargs)	Call self as a function.
call(optimizer, cost, trainables, **kwargs)	Logs costs and parameters to Tensorboard.
get_opt_step(optimizer, **kwargs)	Gets current step from optimizer.
init_writer(trainables)	Initializes tb logdir folders and writer.
trigger(**kwargs)	User implemented custom trigger conditions.
update_cost_fn(**kwargs)	User implemented cost_fn modifier.
update_grads(**kwargs)	User implemented gradient modifier.
update_optimizer(optimizer, **kwargs)	User implemented optimizer update scheduler.

__call__(**kwargs)

Call self as a function.

call(optimizer, cost, trainables, **kwargs)

Logs costs and parameters to Tensorboard.

get_opt_step(optimizer, **kwargs)

Gets current step from optimizer.

init_writer(trainables)

Initializes tb logdir folders and writer.

trigger(**kwargs)

User implemented custom trigger conditions.

Return type:

bool

update_cost_fn(**kwargs)

User implemented cost_fn modifier.

Return type:

Optional[Callable]

update_grads(**kwargs)

User implemented gradient modifier.

Return type:

Optional[Sequence]

update_optimizer(optimizer, **kwargs)

User implemented optimizer update scheduler.

code/api/mrmustard.training.callbacks.TensorboardCallback

 

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