VisionTransformerClsHead

class mmpretrain.models.heads.VisionTransformerClsHead(num_classes, in_channels, hidden_dim=None, act_cfg={'type': 'Tanh'}, init_cfg={'layer': 'Linear', 'type': 'Constant', 'val': 0}, **kwargs)

Vision Transformer classifier head.

参数:

• num_classes (int) – Number of categories excluding the background category.

• in_channels (int) – Number of channels in the input feature map.

• hidden_dim (int, optional) – Number of the dimensions for hidden layer. Defaults to None, which means no extra hidden layer.

• act_cfg (dict) – The activation config. Only available during pre-training. Defaults to dict(type='Tanh').

• init_cfg (dict) – The extra initialization configs. Defaults to dict(type='Constant', layer='Linear', val=0).

forward(feats)

The forward process.

init_weights()

“Init weights of hidden layer if exists.

pre_logits(feats)

The process before the final classification head.

The input feats is a tuple of list of tensor, and each tensor is the feature of a backbone stage. In VisionTransformerClsHead, we obtain the feature of the last stage and forward in hidden layer if exists.