Source code for mmselfsup.models.heads.maskfeat_head
# Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmengine.model import BaseModule
from mmselfsup.registry import MODELS
[docs]@MODELS.register_module()
class MaskFeatPretrainHead(BaseModule):
"""Pre-training head for MaskFeat.
It computes reconstruction loss between prediction and target in masked
region.
Args:
loss (dict): Config dict for module of loss functions.
"""
def __init__(self, loss: dict) -> None:
super().__init__()
self.loss = MODELS.build(loss)
[docs] def forward(self, pred: torch.Tensor, target: torch.Tensor,
mask: torch.Tensor) -> torch.Tensor:
"""Forward head.
Args:
latent (torch.Tensor): Predictions,
which is of shape B x (1 + L) x C.
target (torch.Tensor): Hog features, which is of shape B x L x C.
mask (torch.Tensor): The mask of the hog features,
which is of shape B x H x W.
Returns:
torch.Tensor: The loss tensor.
"""
mask = mask.flatten(1).bool()
loss = self.loss(pred[:, 1:], target, mask)
return loss