torch_frame.nn.decoder.TromptDecoder

class TromptDecoder(in_channels: int, out_channels: int, num_prompts: int)

Bases: Decoder

The Trompt downstream introduced in “Trompt: Towards a Better Deep Neural Network for Tabular Data” paper.

Parameters:

• in_channels (int) – Input channel dimensionality

• out_channels (int) – Output channel dimensionality

• num_prompts (int) – Number of prompt columns.

reset_parameters() → None

Resets all learnable parameters of the module.

forward(x: Tensor) → Tensor

Decode x of shape [batch_size, num_cols, channels] into an output tensor of shape [batch_size, out_channels].

Parameters:

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

• args (Any) – Extra arguments.

• kwargs (Any) – Extra keyward arguments.