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* Rename all MDX file to `.mdx`
* Lock current node version (#11885)
* Apply Prettier (#11996)
* Minor website fixes (#11974) [ci skip]
* fix table
* Migrate to Next WEB-17 (#12005)
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Following: 77b5f79a4d/packages/next-mdx/readme.md
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Before `h1` components where not overwritten and would never have worked and they aren't used anywhere either.
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* Fix invalid code language
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* Enable code blocks plugin
* Readd `InlineCode` component
MDX2 removed the `inlineCode` component
> The special component name `inlineCode` was removed, we recommend to use `pre` for the block version of code, and code for both the block and inline versions
Source: https://mdxjs.com/migrating/v2/#update-mdx-content
* Remove unused code
* Extract function to own file
* Fix code syntax highlighting
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* Fix internal link recognition
There is a problem with regex between Node and browser, and since Next runs the component on both, this create an error.
`Prop `rel` did not match. Server: "null" Client: "noopener nofollow noreferrer"`
This simplifies the implementation and fixes the above error.
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* Fix problem with `span` inside inline `code`
React doesn't allow a `span` inside an inline `code` element and throws an error in dev mode.
* Add `_document` to be able to customize `<html>` and `<body>`
* Add `lang="en"`
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* Fix bug with anchor links after reloading
There was no need for the previous implementation, since the browser handles this nativly. Additional the manual scrolling into view was actually broken, because the heading would disappear behind the menu bar.
* Rename custom event
I was googeling for ages to find out what kind of event `inview` is, only to figure out it was a custom event with a name that sounds pretty much like a native one. 🫠
* Fix missing comment syntax highlighting
* Refactor Quickstart component
The previous implementation was hidding the irrelevant lines via data-props and dynamically generated CSS. This created problems with Next and was also hard to follow. CSS was used to do what React is supposed to handle.
The new implementation simplfy filters the list of children (React elements) via their props.
* Fix syntax highlighting for Training Quickstart
* Unify code rendering
* Improve error logging in Juniper
* Fix Juniper component
* Automatically generate "Read Next" link
* Add Plausible
* Use recent DocSearch component and adjust styling
* Fix images
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> Image Optimization using Next.js' default loader is not compatible with `next export`.
We currently deploy to Netlify via `next export`
* Dont build pages starting with `_`
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* Add Next plugin to Netlify
* Fix button layout
MDX automatically adds `p` tags around text on a new line and Prettier wants to put the text on a new line. Hacking with JSX string.
* Add 404 page
* Apply Prettier
* Update Prettier for `package.json`
Next sometimes wants to patch `package-lock.json`. The old Prettier setting indended with 4 spaces, but Next always indends with 2 spaces. Since `npm install` automatically uses the indendation from `package.json` for `package-lock.json` and to avoid the format switching back and forth, both files are now set to 2 spaces.
* Apply Next patch to `package-lock.json`
When starting the dev server Next would warn `warn - Found lockfile missing swc dependencies, patching...` and update the `package-lock.json`. These are the patched changes.
* fix link
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* small backslash fixes
* adjust to new style
Co-authored-by: Marcus Blättermann <marcus@essenmitsosse.de>
268 lines
15 KiB
Plaintext
268 lines
15 KiB
Plaintext
---
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title: AttributeRuler
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tag: class
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source: spacy/pipeline/attributeruler.py
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version: 3
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teaser: 'Pipeline component for rule-based token attribute assignment'
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api_string_name: attribute_ruler
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api_trainable: false
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---
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The attribute ruler lets you set token attributes for tokens identified by
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[`Matcher` patterns](/usage/rule-based-matching#matcher). The attribute ruler is
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typically used to handle exceptions for token attributes and to map values
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between attributes such as mapping fine-grained POS tags to coarse-grained POS
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tags. See the [usage guide](/usage/linguistic-features/#mappings-exceptions) for
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examples.
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## Config and implementation {id="config"}
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The default config is defined by the pipeline component factory and describes
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how the component should be configured. You can override its settings via the
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`config` argument on [`nlp.add_pipe`](/api/language#add_pipe) or in your
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[`config.cfg` for training](/usage/training#config).
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> #### Example
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>
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> ```python
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> config = {"validate": True}
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> nlp.add_pipe("attribute_ruler", config=config)
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> ```
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| Setting | Description |
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| ---------- | --------------------------------------------------------------------------------------------- |
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| `validate` | Whether patterns should be validated (passed to the `Matcher`). Defaults to `False`. ~~bool~~ |
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```python
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%%GITHUB_SPACY/spacy/pipeline/attributeruler.py
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```
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## AttributeRuler.\_\_init\_\_ {id="init",tag="method"}
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Initialize the attribute ruler.
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> #### Example
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>
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> ```python
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> # Construction via add_pipe
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> ruler = nlp.add_pipe("attribute_ruler")
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> ```
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| Name | Description |
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| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `vocab` | The shared vocabulary to pass to the matcher. ~~Vocab~~ |
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| `name` | Instance name of the current pipeline component. Typically passed in automatically from the factory when the component is added. ~~str~~ |
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| _keyword-only_ | |
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| `validate` | Whether patterns should be validated (passed to the [`Matcher`](/api/matcher#init)). Defaults to `False`. ~~bool~~ |
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| `scorer` | The scoring method. Defaults to [`Scorer.score_token_attr`](/api/scorer#score_token_attr) for the attributes `"tag`", `"pos"`, `"morph"` and `"lemma"` and [`Scorer.score_token_attr_per_feat`](/api/scorer#score_token_attr_per_feat) for the attribute `"morph"`. ~~Optional[Callable]~~ |
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## AttributeRuler.\_\_call\_\_ {id="call",tag="method"}
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Apply the attribute ruler to a `Doc`, setting token attributes for tokens
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matched by the provided patterns.
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| Name | Description |
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| ----------- | -------------------------------- |
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| `doc` | The document to process. ~~Doc~~ |
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| **RETURNS** | The processed document. ~~Doc~~ |
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## AttributeRuler.add {id="add",tag="method"}
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Add patterns to the attribute ruler. The patterns are a list of `Matcher`
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patterns and the attributes are a dict of attributes to set on the matched
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token. If the pattern matches a span of more than one token, the `index` can be
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used to set the attributes for the token at that index in the span. The `index`
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may be negative to index from the end of the span.
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> patterns = [[{"TAG": "VB"}]]
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> attrs = {"POS": "VERB"}
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> ruler.add(patterns=patterns, attrs=attrs)
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> ```
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| Name | Description |
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| ---------- | --------------------------------------------------------------------------------------------------------------------------------- |
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| `patterns` | The `Matcher` patterns to add. ~~Iterable[List[Dict[Union[int, str], Any]]]~~ |
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| `attrs` | The attributes to assign to the target token in the matched span. ~~Dict[str, Any]~~ |
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| `index` | The index of the token in the matched span to modify. May be negative to index from the end of the span. Defaults to `0`. ~~int~~ |
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## AttributeRuler.add_patterns {id="add_patterns",tag="method"}
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> patterns = [
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> {
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> "patterns": [[{"TAG": "VB"}]], "attrs": {"POS": "VERB"}
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> },
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> {
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> "patterns": [[{"LOWER": "two"}, {"LOWER": "apples"}]],
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> "attrs": {"LEMMA": "apple"},
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> "index": -1
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> },
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> ]
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> ruler.add_patterns(patterns)
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> ```
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Add patterns from a list of pattern dicts. Each pattern dict can specify the
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keys `"patterns"`, `"attrs"` and `"index"`, which match the arguments of
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[`AttributeRuler.add`](/api/attributeruler#add).
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| Name | Description |
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| ---------- | -------------------------------------------------------------------------- |
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| `patterns` | The patterns to add. ~~Iterable[Dict[str, Union[List[dict], dict, int]]]~~ |
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## AttributeRuler.patterns {id="patterns",tag="property"}
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Get all patterns that have been added to the attribute ruler in the
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`patterns_dict` format accepted by
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[`AttributeRuler.add_patterns`](/api/attributeruler#add_patterns).
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| Name | Description |
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| ----------- | -------------------------------------------------------------------------------------------- |
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| **RETURNS** | The patterns added to the attribute ruler. ~~List[Dict[str, Union[List[dict], dict, int]]]~~ |
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## AttributeRuler.initialize {id="initialize",tag="method"}
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Initialize the component with data and used before training to load in rules
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from a file. This method is typically called by
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[`Language.initialize`](/api/language#initialize) and lets you customize
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arguments it receives via the
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[`[initialize.components]`](/api/data-formats#config-initialize) block in the
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config.
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> ruler.initialize(lambda: [], nlp=nlp, patterns=patterns)
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> ```
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>
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> ```ini
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> ### config.cfg
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> [initialize.components.attribute_ruler]
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>
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> [initialize.components.attribute_ruler.patterns]
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> @readers = "srsly.read_json.v1"
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> path = "corpus/attribute_ruler_patterns.json
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> ```
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| Name | Description |
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| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects (the training data). Not used by this component. ~~Callable[[], Iterable[Example]]~~ |
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| _keyword-only_ | |
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| `nlp` | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~ |
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| `patterns` | A list of pattern dicts with the keys as the arguments to [`AttributeRuler.add`](/api/attributeruler#add) (`patterns`/`attrs`/`index`) to add as patterns. Defaults to `None`. ~~Optional[Iterable[Dict[str, Union[List[dict], dict, int]]]]~~ |
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| `tag_map` | The tag map that maps fine-grained tags to coarse-grained tags and morphological features. Defaults to `None`. ~~Optional[Dict[str, Dict[Union[int, str], Union[int, str]]]]~~ |
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| `morph_rules` | The morph rules that map token text and fine-grained tags to coarse-grained tags, lemmas and morphological features. Defaults to `None`. ~~Optional[Dict[str, Dict[str, Dict[Union[int, str], Union[int, str]]]]]~~ |
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## AttributeRuler.load_from_tag_map {id="load_from_tag_map",tag="method"}
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Load attribute ruler patterns from a tag map.
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| Name | Description |
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| --------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `tag_map` | The tag map that maps fine-grained tags to coarse-grained tags and morphological features. ~~Dict[str, Dict[Union[int, str], Union[int, str]]]~~ |
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## AttributeRuler.load_from_morph_rules {id="load_from_morph_rules",tag="method"}
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Load attribute ruler patterns from morph rules.
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| Name | Description |
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| ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `morph_rules` | The morph rules that map token text and fine-grained tags to coarse-grained tags, lemmas and morphological features. ~~Dict[str, Dict[str, Dict[Union[int, str], Union[int, str]]]]~~ |
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## AttributeRuler.to_disk {id="to_disk",tag="method"}
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Serialize the pipe to disk.
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> ruler.to_disk("/path/to/attribute_ruler")
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> ```
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| Name | Description |
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| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
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| `path` | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
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| _keyword-only_ | |
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| `exclude` | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
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## AttributeRuler.from_disk {id="from_disk",tag="method"}
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Load the pipe from disk. Modifies the object in place and returns it.
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> ruler.from_disk("/path/to/attribute_ruler")
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> ```
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| Name | Description |
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| -------------- | ----------------------------------------------------------------------------------------------- |
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| `path` | A path to a directory. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
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| _keyword-only_ | |
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| `exclude` | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
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| **RETURNS** | The modified `AttributeRuler` object. ~~AttributeRuler~~ |
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## AttributeRuler.to_bytes {id="to_bytes",tag="method"}
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> #### Example
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>
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> ```python
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> ruler = nlp.add_pipe("attribute_ruler")
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> ruler = ruler.to_bytes()
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> ```
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Serialize the pipe to a bytestring.
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| Name | Description |
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| -------------- | ------------------------------------------------------------------------------------------- |
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| _keyword-only_ | |
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| `exclude` | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
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| **RETURNS** | The serialized form of the `AttributeRuler` object. ~~bytes~~ |
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## AttributeRuler.from_bytes {id="from_bytes",tag="method"}
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Load the pipe from a bytestring. Modifies the object in place and returns it.
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> #### Example
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>
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> ```python
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> ruler_bytes = ruler.to_bytes()
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> ruler = nlp.add_pipe("attribute_ruler")
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> ruler.from_bytes(ruler_bytes)
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> ```
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| Name | Description |
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| -------------- | ------------------------------------------------------------------------------------------- |
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| `bytes_data` | The data to load from. ~~bytes~~ |
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| _keyword-only_ | |
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| `exclude` | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
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| **RETURNS** | The `AttributeRuler` object. ~~AttributeRuler~~ |
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## Serialization fields {id="serialization-fields"}
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During serialization, spaCy will export several data fields used to restore
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different aspects of the object. If needed, you can exclude them from
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serialization by passing in the string names via the `exclude` argument.
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> #### Example
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>
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> ```python
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> data = ruler.to_disk("/path", exclude=["vocab"])
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> ```
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| Name | Description |
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| ---------- | --------------------------------------------------------------- |
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| `vocab` | The shared [`Vocab`](/api/vocab). |
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| `patterns` | The `Matcher` patterns. You usually don't want to exclude this. |
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| `attrs` | The attributes to set. You usually don't want to exclude this. |
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| `indices` | The token indices. You usually don't want to exclude this. |
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