mm.training.callbacks.Callback

class mrmustard.training.callbacks.Callback(tag=None, steps_per_call=1)

Bases: object

Base callback class for optimizers. Users can inherit from this class and define the following custom logic:

• .trigger:

  Custom triggering condition, other than the regular schedule set by step_per_call.

• .call:

  The main routine to be customized.

• .update_cost_fn:

  The custom cost_fn updater, which is expected to return a new cost_fn callable to replace the original one passed to the optimizer.

• .update_grads:

  The custom grads modifyer, which is expected to return a list of parameter gradients after modification, to be applied to the parameters.

• .update_optimizer:

  The custom optimizer updater, which is expected to modify the optimizer inplace for things like scheduling learning rates.

Attributes

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.

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.

Methods

__call__(**kwargs)	Call self as a function.
call(**kwargs)	User implemented main callback logic.
get_opt_step(optimizer, **kwargs)	Gets current step from optimizer.
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(**kwargs)

User implemented main callback logic.

Return type:

Optional[Mapping]

get_opt_step(optimizer, **kwargs)

Gets current step from optimizer.

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.

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