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mmselfsup.models.heads.simmim_head 源代码
# Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.runner import BaseModule
from torch.nn import functional as F
from ..builder import HEADS
[文档]@HEADS.register_module()
class SimMIMHead(BaseModule):
"""Pretrain Head for SimMIM.
Args:
patch_size (int): Patch size of each token.
encoder_in_channels (int): Number of input channels for encoder.
"""
def __init__(self, patch_size: int, encoder_in_channels: int) -> None:
super(SimMIMHead, self).__init__()
self.patch_size = patch_size
self.encoder_in_channels = encoder_in_channels
[文档] def forward(self, x: torch.Tensor, x_rec: torch.Tensor,
mask: torch.Tensor) -> dict:
losses = dict()
mask = mask.repeat_interleave(self.patch_size, 1).repeat_interleave(
self.patch_size, 2).unsqueeze(1).contiguous()
loss_rec = F.l1_loss(x, x_rec, reduction='none')
loss = (loss_rec * mask).sum() / (mask.sum() +
1e-5) / self.encoder_in_channels
losses['loss'] = loss
return losses