flambe.nn.cnn

Module Contents

flambe.nn.cnn.conv_block(conv_mod: nn.Module, activation: nn.Module, pooling: nn.Module, dropout: float, batch_norm: Optional[nn.Module] = None) → nn.Module[source]

Return a convolutional block.

class flambe.nn.cnn.CNNEncoder(input_channels: int, channels: List[int], conv_dim: int = 2, kernel_size: Union[int, List[Union[Tuple[int, ...], int]]] = 3, activation: nn.Module = None, pooling: nn.Module = None, dropout: float = 0, batch_norm: bool = True, stride: int = 1, padding: int = 0)[source]

Bases: flambe.nn.module.Module

Implements a multi-layer n-dimensional CNN.

This module can be used to create multi-layer CNN models.

cnn

The cnn submodule

Type:nn.Module
forward(self, data: Tensor)[source]

Performs a forward pass through the network.

Parameters:data (torch.Tensor) – The input data, as a float tensor
Returns:The encoded output, as a float tensor
Return type:Union[Tensor, Tuple[Tensor, ..]]