Positional Embedding

class vformer.encoder.embedding.pos_embedding.PVTPosEmbedding(pos_shape, pos_dim, p_dropout=0.0, std=0.02)

Positional Embedding class used in Pyramid vision transformer.

Parameters

• pos_shape (int or tuple(int)) – The shape of the absolute position embedding.

• pos_dim (int) – The dimension of the absolute position embedding.

• p_dropout (float, optional) – Probability of an element to be zeroed, default is 0.2

• std (float) – Standard deviation for truncated normal distribution

forward(x, H, W, mode='bilinear')

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

resize_pos_embed(pos_embed, shape, mode='bilinear', **kwargs)

Parameters

• pos_embed (torch.Tensor) – Position embedding weights

• shape (tuple) – Required shape

• mode (str (nearest | linear | bilinear | bicubic | trilinear )) – Algorithm used for up/down sampling, default is bilinear.

class vformer.encoder.embedding.pos_embedding.PosEmbedding(shape, dim, drop=None, sinusoidal=False, std=0.02)

Generalised Positional Embedding class

forward(x)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.