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extra/DEVELOPER_DOCS/Listeners.md
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@ -1,14 +1,18 @@
# Listeners
1. [Overview](#1-overview)
2. [Initialization](#2-initialization)
- [A. Linking listeners to the embedding component](#2a-linking-listeners-to-the-embedding-component)
- [B. Shape inference](#2b-shape-inference)
3. [Internal communication](#3-internal-communication)
- [A. During prediction](#3a-during-prediction)
- [B. During training](#3b-during-training)
- [C. Frozen components](#3c-frozen-components)
4. [Replacing listener with standalone](#4-replacing-listener-with-standalone)
- [Listeners](#listeners)
- [1. Overview](#1-overview)
- [2. Initialization](#2-initialization)
- [2A. Linking listeners to the embedding component](#2a-linking-listeners-to-the-embedding-component)
- [2B. Shape inference](#2b-shape-inference)
- [3. Internal communication](#3-internal-communication)
- [3A. During prediction](#3a-during-prediction)
- [3B. During training](#3b-during-training)
- [Training with multiple listeners](#training-with-multiple-listeners)
- [3C. Frozen components](#3c-frozen-components)
- [The Tok2Vec or Transformer is frozen](#the-tok2vec-or-transformer-is-frozen)
- [The upstream component is frozen](#the-upstream-component-is-frozen)
- [4. Replacing listener with standalone](#4-replacing-listener-with-standalone)
## 1. Overview
@ -62,7 +66,7 @@ of this `find_listener()` method will specifically identify sublayers of a model
If it's a Transformer-based pipeline, a
[`transformer` component](https://github.com/explosion/spacy-transformers/blob/master/spacy_transformers/pipeline_component.py)
has a similar implementation but its `find_listener()` function will specifically look for `TransformerListener`
has a similar implementation but its `find_listener()` function will specifically look for `TransformerListener`
sublayers of downstream components.
### 2B. Shape inference
@ -154,7 +158,7 @@ as a tagger or a parser. This used to be impossible before 3.1, but has become s
embedding component in the [`annotating_components`](https://spacy.io/usage/training#annotating-components)
list of the config. This works like any other "annotating component" because it relies on the `Doc` attributes.
However, if the `Tok2Vec` or `Transformer` is frozen, and not present in `annotating_components`, and a related
However, if the `Tok2Vec` or `Transformer` is frozen, and not present in `annotating_components`, and a related
listener isn't frozen, then a `W086` warning is shown and further training of the pipeline will likely end with `E954`.
#### The upstream component is frozen
@ -216,5 +220,12 @@ new_model = tok2vec_model.attrs["replace_listener"](new_model)
```
The new config and model are then properly stored on the `nlp` object.
Note that this functionality (running the replacement for a transformer listener) was broken prior to
Note that this functionality (running the replacement for a transformer listener) was broken prior to
`spacy-transformers` 1.0.5.
As of spaCy 3.7, the `replace_listener` callback accepts three arguments instead of just one: the new (copied) model,
the listener to be replaced, the `tok2vec`/`transformer` pipe from which the new model was copied.
```
new_model = tok2vec_model.attrs["replace_listener"](new_model, replaced_listener, tok2vec)
```