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mmpretrain.models.heads.mixmim_head 源代码

# Copyright (c) OpenMMLab. All rights reserved.
import torch

from mmpretrain.registry import MODELS
from .mae_head import MAEPretrainHead


[文档]@MODELS.register_module() class MixMIMPretrainHead(MAEPretrainHead): """Head for MixMIM Pre-training. Args: loss (dict): Config of loss. norm_pix_loss (bool): Whether or not normalize target. Defaults to False. patch_size (int): Patch size. Defaults to 16. """ def __init__(self, loss: dict, norm_pix: bool = False, patch_size: int = 16) -> None: super().__init__(loss=loss, norm_pix=norm_pix, patch_size=patch_size)
[文档] def loss(self, x_rec: torch.Tensor, target: torch.Tensor, mask: torch.Tensor) -> torch.Tensor: """Generate loss. Args: pred (torch.Tensor): The reconstructed image. target (torch.Tensor): The target image. mask (torch.Tensor): The mask of the target image. Returns: torch.Tensor: The reconstruction loss. """ target = self.construct_target(target) B, L, C = x_rec.shape # unmix tokens x1_rec = x_rec[:B // 2] x2_rec = x_rec[B // 2:] unmix_x_rec = x1_rec * mask + x2_rec.flip(0) * (1 - mask) loss_rec = self.loss_module(unmix_x_rec, target) return loss_rec
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