SATRNEncoder

class mmocr.models.textrecog.SATRNEncoder(n_layers=12, n_head=8, d_k=64, d_v=64, d_model=512, n_position=100, d_inner=256, dropout=0.1, init_cfg=None)

Implement encoder for SATRN, see `SATRN.

<https://arxiv.org/abs/1910.04396>`_.

Parameters

• n_layers (int) – Number of attention layers. Defaults to 12.

• n_head (int) – Number of parallel attention heads. Defaults to 8.

• d_k (int) – Dimension of the key vector. Defaults to 64.

• d_v (int) – Dimension of the value vector. Defaults to 64.

• d_model (int) – Dimension \(D_m\) of the input from previous model. Defaults to 512.

• n_position (int) – Length of the positional encoding vector. Must be greater than max_seq_len. Defaults to 100.

• d_inner (int) – Hidden dimension of feedforward layers. Defaults to 256.

• dropout (float) – Dropout rate. Defaults to 0.1.

• init_cfg (dict or list[dict], optional) – Initialization configs. Defaults to None.

Return type

None

forward(feat, data_samples=None)

Forward propagation of encoder.

Parameters

• feat (Tensor) – Feature tensor of shape \((N, D_m, H, W)\).

• data_samples (list[TextRecogDataSample]) – Batch of TextRecogDataSample, containing valid_ratio information. Defaults to None.

Returns

A tensor of shape \((N, T, D_m)\).

Return type

Tensor