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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)[源代码]

Implement encoder for SATRN, see `SATRN.

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

参数
  • 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.

返回类型

None

forward(feat, data_samples=None)[源代码]

Forward propagation of encoder.

参数
  • 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.

返回

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

返回类型

Tensor

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