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mmcls.models.VisionTransformer

class mmcls.models.VisionTransformer(arch='base', img_size=224, patch_size=16, in_channels=3, out_indices=- 1, drop_rate=0.0, drop_path_rate=0.0, qkv_bias=True, norm_cfg={'eps': 1e-06, 'type': 'LN'}, final_norm=True, with_cls_token=True, output_cls_token=True, interpolate_mode='bicubic', patch_cfg={}, layer_cfgs={}, init_cfg=None)

Vision Transformer.

A PyTorch implement of : An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

参数

• arch (str | dict) –

  Vision Transformer architecture. If use string, choose from ‘small’, ‘base’, ‘large’, ‘deit-tiny’, ‘deit-small’ and ‘deit-base’. If use dict, it should have below keys:

  • embed_dims (int): The dimensions of embedding.

  • num_layers (int): The number of transformer encoder layers.

  • num_heads (int): The number of heads in attention modules.

  • feedforward_channels (int): The hidden dimensions in feedforward modules.

  Defaults to ‘base’.

• img_size (int | tuple) – The expected input image shape. Because we support dynamic input shape, just set the argument to the most common input image shape. Defaults to 224.

• patch_size (int | tuple) – The patch size in patch embedding. Defaults to 16.

• in_channels (int) – The num of input channels. Defaults to 3.

• out_indices (Sequence | int) – Output from which stages. Defaults to -1, means the last stage.

• drop_rate (float) – Probability of an element to be zeroed. Defaults to 0.

• drop_path_rate (float) – stochastic depth rate. Defaults to 0.

• qkv_bias (bool) – Whether to add bias for qkv in attention modules. Defaults to True.

• norm_cfg (dict) – Config dict for normalization layer. Defaults to dict(type='LN').

• final_norm (bool) – Whether to add a additional layer to normalize final feature map. Defaults to True.

• with_cls_token (bool) – Whether concatenating class token into image tokens as transformer input. Defaults to True.

• output_cls_token (bool) – Whether output the cls_token. If set True, with_cls_token must be True. Defaults to True.

• interpolate_mode (str) – Select the interpolate mode for position embeding vector resize. Defaults to “bicubic”.

• patch_cfg (dict) – Configs of patch embeding. Defaults to an empty dict.

• layer_cfgs (Sequence | dict) – Configs of each transformer layer in encoder. Defaults to an empty dict.

• init_cfg (dict, optional) – Initialization config dict. Defaults to None.