Module providing Consciousness Exploration Tools for PyTorch.
Note
This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the gallery for the big picture.
-
class
consciousnet.models.BarlowTwins(model, fc_layer_name, fc_in_features, projector, batch_size, lambd)[source]¶ Barlow Twins: Self-Supervised Learning via Redundancy Reduction.
-
__init__(model, fc_layer_name, fc_in_features, projector, batch_size, lambd)[source]¶ Init class.
- Parameters
model : nn.model
the classification network.
fc_layer_name : str
the name of the fully conencted layer that will be replaced during the optimization by a projection head.
fc_in_features : int
the fully connected input features dimension.
projector : str
the MLP layers projector definition of the form 120-120-120.
batch_size : int
the mini-batch size.
lambd : float
the weight applied on off-diagonal terms.
-
Follow us