Text CNN[source]

The eds.text_cnn component is a simple 1D convolutional network to contextualize word embeddings (as computed by the embedding component passed as argument).

To be memory efficient when handling batches of variable-length sequences, this module employs sequence packing, while taking care of avoiding contamination between the different docs.

Parameters

PARAMETER	DESCRIPTION
`nlp`	The pipeline object TYPE: `PipelineProtocol`
`name`	The name of the component TYPE: `str`
`embedding`	Embedding module to apply to the input TYPE: `TorchComponent[WordEmbeddingBatchOutput, BatchInput]`
`output_size`	Size of the output embeddings Defaults to the `input_size` TYPE: `Optional[int]` DEFAULT: `None`
`out_channels`	Number of channels TYPE: `int` DEFAULT: `None`
`kernel_sizes`	Window size of each kernel TYPE: `Sequence[int]` DEFAULT: `(3, 4, 5)`
`activation`	Activation function to use TYPE: `str` DEFAULT: `relu`
`residual`	Whether to use residual connections TYPE: `bool` DEFAULT: `True`
`normalize`	Whether to normalize before or after the residual connection TYPE: `Literal['pre', 'post', 'none']` DEFAULT: `pre`