flambe.nlp.classification.model

Module Contents

class flambe.nlp.classification.model.TextClassifier(embedder: Embedder, output_layer: Module, dropout: float = 0)[source]

Bases: flambe.nn.Module

Implements a standard classifier.

The classifier is composed of an encoder module, followed by a fully connected output layer, with a dropout layer in between.

embedder

The embedder layer

Type:Embedder
output_layer

The output layer, yields a probability distribution over targets

Type:Module
drop

the dropout layer

Type:nn.Dropout
loss

the loss function to optimize the model with

Type:Metric
metric

the dev metric to evaluate the model on

Type:Metric
forward(self, data: Tensor, target: Optional[Tensor] = None)[source]

Run a forward pass through the network.

Parameters:
  • data (Tensor) – The input data
  • target (Tensor, optional) – The input targets, optional
Returns:

The output predictions, and optionally the targets

Return type:

Union[Tensor, Tuple[Tensor, Tensor]