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Improve section on disabling pipes [ci skip]

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Ines Montani 2019-07-25 14:25:34 +02:00
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website/docs/usage/processing-pipelines.md
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@ -146,19 +146,56 @@ require them in the pipeline settings in your model's `meta.json`.
### Disabling and modifying pipeline components {#disabling} ### Disabling and modifying pipeline components {#disabling}
If you don't need a particular component of the pipeline – for example, the If you don't need a particular component of the pipeline – for example, the
tagger or the parser, you can disable loading it. This can sometimes make a big tagger or the parser, you can **disable loading** it. This can sometimes make a
difference and improve loading speed. Disabled component names can be provided big difference and improve loading speed. Disabled component names can be
to [`spacy.load`](/api/top-level#spacy.load), provided to [`spacy.load`](/api/top-level#spacy.load),
[`Language.from_disk`](/api/language#from_disk) or the `nlp` object itself as a [`Language.from_disk`](/api/language#from_disk) or the `nlp` object itself as a
list: list:
```python ```python
nlp = spacy.load("en", disable=["parser", "tagger"]) ### Disable loading
nlp = spacy.load("en_core_web_sm", disable=["tagger", "parser"])
nlp = English().from_disk("/model", disable=["ner"]) nlp = English().from_disk("/model", disable=["ner"])
``` ```
You can also use the [`remove_pipe`](/api/language#remove_pipe) method to remove In some cases, you do want to load all pipeline components and their weights,
pipeline components from an existing pipeline, the because you need them at different points in your application. However, if you
only need a `Doc` object with named entities, there's no need to run all
pipeline components on it – that can potentially make processing much slower.
Instead, you can use the `disable` keyword argument on
[`nlp.pipe`](/api/language#pipe) to temporarily disable the components **during
processing**:
```python
### Disable for processing
for doc in nlp.pipe(texts, disable=["tagger", "parser"]):
# Do something with the doc here
```
If you need to **execute more code** with components disabled – e.g. to reset
the weights or update only some components during training – you can use the
[`nlp.disable_pipes`](/api/language#disable_pipes) contextmanager. At the end of
the `with` block, the disabled pipeline components will be restored
automatically. Alternatively, `disable_pipes` returns an object that lets you
call its `restore()` method to restore the disabled components when needed. This
can be useful if you want to prevent unnecessary code indentation of large
blocks.
```python
### Disable for block
# 1. Use as a contextmanager
with nlp.disable_pipes("tagger", "parser"):
doc = nlp(u"I won't be tagged and parsed")
doc = nlp(u"I will be tagged and parsed")
# 2. Restore manually
disabled = nlp.disable_pipes("ner")
doc = nlp(u"I won't have named entities")
disabled.restore()
```
Finally, you can also use the [`remove_pipe`](/api/language#remove_pipe) method
to remove pipeline components from an existing pipeline, the
[`rename_pipe`](/api/language#rename_pipe) method to rename them, or the [`rename_pipe`](/api/language#rename_pipe) method to rename them, or the
[`replace_pipe`](/api/language#replace_pipe) method to replace them with a [`replace_pipe`](/api/language#replace_pipe) method to replace them with a
custom component entirely (more details on this in the section on custom component entirely (more details on this in the section on