coral_loss

CORALLoss

Bases: torch.nn.Module

Implementation of Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Source code in pytorch_adapt\layers\coral_loss.py

class CORALLoss(torch.nn.Module):
    """
    Implementation of [Deep CORAL:
    Correlation Alignment for
    Deep Domain Adaptation](https://arxiv.org/abs/1607.01719)
    """

    def forward(self, x: torch.Tensor, y: torch.Tensor):
        """
        Arguments:
            x: features from one domain
            y: features from the other domain
        """
        embedding_size = x.shape[1]
        cx = covariance(x)
        cy = covariance(y)
        squared_fro_norm = torch.linalg.norm(cx - cy, ord="fro") ** 2
        return squared_fro_norm / (4 * (embedding_size**2))

forward(x, y)

Parameters:

Name	Type	Description	Default
x	torch.Tensor	features from one domain	required
y	torch.Tensor	features from the other domain	required

Source code in pytorch_adapt\layers\coral_loss.py

def forward(self, x: torch.Tensor, y: torch.Tensor):
    """
    Arguments:
        x: features from one domain
        y: features from the other domain
    """
    embedding_size = x.shape[1]
    cx = covariance(x)
    cy = covariance(y)
    squared_fro_norm = torch.linalg.norm(cx - cy, ord="fro") ** 2
    return squared_fro_norm / (4 * (embedding_size**2))