inFairness.distances.distance module#

class inFairness.distances.distance.Distance[source]#

Bases: Module

Abstract base class for model distances

fit(**kwargs)[source]#

Fits the metric parameters for learnable metrics Default functionality is to do nothing. Subclass should overwrite this method to implement custom fit logic

abstract forward(x, y)[source]#

Subclasses must override this method to compute particular distances

Returns:

distance between two inputs

Return type:

Tensor

load_state_dict(state_dict, strict=True)[source]#

Copies parameters and buffers from state_dict into this module and its descendants. If strict is True, then the keys of state_dict must exactly match the keys returned by this module’s state_dict() function.

Parameters:

  • state_dict (dict) – a dict containing parameters and persistent buffers.

  • strict (bool, optional) – whether to strictly enforce that the keys in state_dict match the keys returned by this module’s state_dict() function. Default: True

Returns:

  • missing_keys is a list of str containing the missing keys

  • unexpected_keys is a list of str containing the unexpected keys

Return type:

NamedTuple with missing_keys and unexpected_keys fields

Note

If a parameter or buffer is registered as None and its corresponding key exists in state_dict, load_state_dict() will raise a RuntimeError.

training: bool#