From 065aa062f0e33f73e043534445c8636b36778f16 Mon Sep 17 00:00:00 2001 From: richardpaulhudson Date: Sat, 10 Dec 2022 09:52:45 +0100 Subject: [PATCH] Updated documentation --- spacy/ml/models/lemmatizer.py | 1 + website/docs/api/architectures.md | 15 ++++++++------- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/spacy/ml/models/lemmatizer.py b/spacy/ml/models/lemmatizer.py index 14a0c879b..666ea0363 100644 --- a/spacy/ml/models/lemmatizer.py +++ b/spacy/ml/models/lemmatizer.py @@ -30,6 +30,7 @@ def build_lemmatizer_model( tok2vec (Model[List[Doc], List[Floats2d]]): The token-to-vector subnetwork. nO (int or None): The number of tags to output in the main model. Inferred from the data if None. lowercasing: if *True*, the additional sigmoid appendage is created. + lowercasing_relu_width: the width of the linear layer within the sigmoid appendage. """ with Model.define_operators({">>": chain, "|": concatenate}): t2v_width = tok2vec.get_dim("nO") if tok2vec.has_dim("nO") else None diff --git a/website/docs/api/architectures.md b/website/docs/api/architectures.md index 85aa3f0a5..c7157f8dd 100644 --- a/website/docs/api/architectures.md +++ b/website/docs/api/architectures.md @@ -677,13 +677,14 @@ results than a direct connection. A possible intuition explaining this is that it reduces the interference between the two learning goals, which are linked but nonetheless distinct. -| Name | Description | -| ------------- | ------------------------------------------------------------------------------------------ | -| `tok2vec` | Subnetwork to map tokens into vector representations. ~~Model[List[Doc], List[Floats2d]]~~ | -| `nO` | The number of tags to output. Inferred from the data if `None`. ~~Optional[int]~~ | -| `normalize` | Normalize probabilities during inference. Defaults to `False`. ~~bool~~ | -| `lowercasing` | If `True`, the additional sigmoid appendage is created. Defaults to `True`. ~~bool~~ | -| **CREATES** | The model using the architecture. ~~Model[List[Doc], List[Floats2d]]~~ | +| Name | Description | +| ------------------------ | ------------------------------------------------------------------------------------------ | +| `tok2vec` | Subnetwork to map tokens into vector representations. ~~Model[List[Doc], List[Floats2d]]~~ | +| `nO` | The number of tags to output. Inferred from the data if `None`. ~~Optional[int]~~ | +| `normalize` | Normalize probabilities during inference. Defaults to `False`. ~~bool~~ | +| `lowercasing` | If `True`, the additional sigmoid appendage is created. Defaults to `True`. ~~bool~~ | +| `lowercasing_relu_width` | The width of the linear layer within the sigmoid appendage. | +| **CREATES** | The model using the architecture. ~~Model[List[Doc], List[Floats2d]]~~ | ## Text classification architectures {#textcat source="spacy/ml/models/textcat.py"}