torch_frame.nn.encoder.EmbeddingEncoder

class EmbeddingEncoder(out_channels: int | None = None, stats_list: list[dict[StatType, Any]] | None = None, stype: stype | None = None, post_module: torch.nn.Module | None = None, na_strategy: NAStrategy | None = None)

Bases: StypeEncoder

An embedding look-up based encoder for categorical features. It applies torch.nn.Embedding for each categorical feature and concatenates the output embeddings.

reset_parameters()

Initialize the parameters of post_module.

encode_forward(feat: Tensor, col_names: list[str] | None = None) → Tensor

The main forward function. Maps input feat from TensorFrame (shape [batch_size, num_cols]) into output x of shape [batch_size, num_cols, out_channels].