context manager with space (for consistency)

This commit is contained in:
svlandeg 2020-08-21 18:34:02 +02:00
parent da48c6a2a2
commit 262552010d
2 changed files with 5 additions and 5 deletions

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@ -265,7 +265,7 @@ for doc in nlp.pipe(texts, disable=["tagger", "parser"]):
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.select_pipes`](/api/language#select_pipes) contextmanager. At the end of
[`nlp.select_pipes`](/api/language#select_pipes) context manager. At the end of
the `with` block, the disabled pipeline components will be restored
automatically. Alternatively, `select_pipes` returns an object that lets you
call its `restore()` method to restore the disabled components when needed. This
@ -274,7 +274,7 @@ blocks.
```python
### Disable for block
# 1. Use as a contextmanager
# 1. Use as a context manager
with nlp.select_pipes(disable=["tagger", "parser"]):
doc = nlp("I won't be tagged and parsed")
doc = nlp("I will be tagged and parsed")

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@ -249,7 +249,7 @@ The following methods, attributes and commands are new in spaCy v3.0.
| ----------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| [`Token.lex`](/api/token#attributes) | Access a token's [`Lexeme`](/api/lexeme). |
| [`Token.morph`](/api/token#attributes) [`Token.morph_`](/api/token#attributes) | Access a token's morphological analysis. |
| [`Language.select_pipes`](/api/language#select_pipes) | Contextmanager for enabling or disabling specific pipeline components for a block. |
| [`Language.select_pipes`](/api/language#select_pipes) | Context manager for enabling or disabling specific pipeline components for a block. |
| [`Language.analyze_pipes`](/api/language#analyze_pipes) | [Analyze](/usage/processing-pipelines#analysis) components and their interdependencies. |
| [`Language.resume_training`](/api/language#resume_training) | Experimental: continue training a pretrained model and initialize "rehearsal" for components that implement a `rehearse` method to prevent catastrophic forgetting. |
| [`@Language.factory`](/api/language#factory) [`@Language.component`](/api/language#component) | Decorators for [registering](/usage/processing-pipelines#custom-components) pipeline component factories and simple stateless component functions. |
@ -336,13 +336,13 @@ Note that spaCy v3.0 now requires **Python 3.6+**.
[training config](/usage/training#config).
- [`Language.add_pipe`](/api/language#add_pipe) now takes the **string name** of
the component factory instead of the component function.
- **Custom pipeline components** now needs to be decorated with the
- **Custom pipeline components** now need to be decorated with the
[`@Language.component`](/api/language#component) or
[`@Language.factory`](/api/language#factory) decorator.
- [`Language.update`](/api/language#update) now takes a batch of
[`Example`](/api/example) objects instead of raw texts and annotations, or
`Doc` and `GoldParse` objects.
- The `Language.disable_pipes` contextmanager has been replaced by
- The `Language.disable_pipes` context manager has been replaced by
[`Language.select_pipes`](/api/language#select_pipes), which can explicitly
disable or enable components.
- The [`Language.update`](/api/language#update),