p2pfl.learning.frameworks.learner module

NodeLearning Interface - Template Pattern.

class p2pfl.learning.frameworks.learner.Learner(model, data, self_addr='unknown-node', aggregator=None)[source]

Bases: ABC

Template to implement learning processes, including metric monitoring during training.

Parameters:

  • model (P2PFLModel) – The model of the learner.

  • data (P2PFLDataset) – The data of the learner.

  • self_addr (str) – The address of the learner.

add_callback_info_to_model()[source]

Add the additional information from the callbacks to the model.

Return type:

None

abstract evaluate()[source]

Evaluate the model with actual parameters.

Return type:

Dict[str, float]

Returns:

The evaluation results.

abstract fit()[source]

Fit the model.

Return type:

P2PFLModel

get_data()[source]

Get the data of the learner.

Return type:

P2PFLDataset

Returns:

The data of the learner.

abstract get_framework()[source]

Retrieve the learner name.

Return type:

str

Returns:

The name of the learner class.

get_model()[source]

Get the model of the learner.

Return type:

P2PFLModel

Returns:

The model of the learner.

abstract interrupt_fit()[source]

Interrupt the fit process.

Return type:

None

set_addr(addr)[source]

Set the address of the learner.

Parameters:

addr (str) – The address of the learner.

Return type:

None

set_data(data)[source]

Set the data of the learner. It is used to fit the model.

Parameters:

data (P2PFLDataset) – The data of the learner.

Return type:

None

set_epochs(epochs)[source]

Set the number of epochs of the model.

Parameters:

epochs (int) – The number of epochs of the model.

Return type:

None

set_model(model)[source]

Set the model of the learner.

Parameters:

model (Union[P2PFLModel, List[ndarray], bytes]) – The model of the learner.

Return type:

None

update_callbacks_with_model_info()[source]

Update the callbacks with the model additional information.

Return type:

None