torch_frame.nn.conv.TabTransformerConv

class TabTransformerConv(channels: int, num_heads: int, attn_dropout: float = 0.0, ffn_dropout: float = 0.0)

Bases: TableConv

The TabTransformer Layer introduced in the “TabTransformer: Tabular Data Modeling Using Contextual Embeddings” paper.

Parameters:

• channels (int) – Input/output channel dimensionality

• num_heads (int) – Number of attention heads

• attn_dropout (float) – attention module dropout (default: 0.)

• ffn_dropout (float) – attention module dropout (default: 0.)

forward(x: Tensor) → Tensor

Process column-wise 3-dimensional tensor into another column-wise 3-dimensional tensor.

Parameters:

• x (torch.Tensor) – Input column-wise tensor of shape [batch_size, num_cols, hidden_channels].

• args (Any) – Extra arguments.

• kwargs (Any) – Extra keyword arguments.

reset_parameters()

Resets all learnable parameters of the module.