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fix link to shape inference section

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svlandeg 2020-09-10 10:22:59 +02:00
parent a25bb50e36
commit 9073d99fc9
7 changed files with 13 additions and 10 deletions
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3
website/docs/api/dependencyparser.md
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@ -297,7 +297,8 @@ Add a new label to the pipe. Note that you don't have to call this method if you
provide a **representative data sample** to the
[`begin_training`](#begin_training) method. In this case, all labels found in
the sample will be automatically added to the model, and the output dimension
will be [inferred](/usage/layers-architectures#shape-inference) automatically.
will be [inferred](/usage/layers-architectures#thinc-shape-inference)
automatically.
> #### Example
>

3
website/docs/api/entityrecognizer.md
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@ -285,7 +285,8 @@ Add a new label to the pipe. Note that you don't have to call this method if you
provide a **representative data sample** to the
[`begin_training`](#begin_training) method. In this case, all labels found in
the sample will be automatically added to the model, and the output dimension
will be [inferred](/usage/layers-architectures#shape-inference) automatically.
will be [inferred](/usage/layers-architectures#thinc-shape-inference)
automatically.
> #### Example
>

4
website/docs/api/language.md
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@ -205,8 +205,8 @@ examples can either be the full training data or a representative sample. They
are used to **initialize the models** of trainable pipeline components and are
passed each component's [`begin_training`](/api/pipe#begin_training) method, if
available. Initialization includes validating the network,
[inferring missing shapes](/usage/layers-architectures#shape-inference) and
setting up the label scheme based on the data.
[inferring missing shapes](/usage/layers-architectures#thinc-shape-inference)
and setting up the label scheme based on the data.
If no `get_examples` function is provided when calling `nlp.begin_training`, the
pipeline components will be initialized with generic data. In this case, it is

3
website/docs/api/morphologizer.md
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@ -263,7 +263,8 @@ already been fully [initialized](#begin_training). Note that you don't have to
call this method if you provide a **representative data sample** to the
[`begin_training`](#begin_training) method. In this case, all labels found in
the sample will be automatically added to the model, and the output dimension
will be [inferred](/usage/layers-architectures#shape-inference) automatically.
will be [inferred](/usage/layers-architectures#thinc-shape-inference)
automatically.
> #### Example
>

2
website/docs/api/pipe.md
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@ -317,7 +317,7 @@ Note that in general, you don't have to call `pipe.add_label` if you provide a
representative data sample to the [`begin_training`](#begin_training) method. In
this case, all labels found in the sample will be automatically added to the
model, and the output dimension will be
[inferred](/usage/layers-architectures#shape-inference) automatically.
[inferred](/usage/layers-architectures#thinc-shape-inference) automatically.
## Pipe.is_resizable {#is_resizable tag="method"}

4
website/docs/api/tagger.md
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@ -293,8 +293,8 @@ set, or if the model has already been fully [initialized](#begin_training). Note
that you don't have to call this method if you provide a **representative data
sample** to the [`begin_training`](#begin_training) method. In this case, all
labels found in the sample will be automatically added to the model, and the
output dimension will be [inferred](/usage/layers-architectures#shape-inference)
automatically.
output dimension will be
[inferred](/usage/layers-architectures#thinc-shape-inference) automatically.
> #### Example
>

4
website/docs/api/textcategorizer.md
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@ -302,8 +302,8 @@ set, or if the model has already been fully [initialized](#begin_training). Note
that you don't have to call this method if you provide a **representative data
sample** to the [`begin_training`](#begin_training) method. In this case, all
labels found in the sample will be automatically added to the model, and the
output dimension will be [inferred](/usage/layers-architectures#shape-inference)
automatically.
output dimension will be
[inferred](/usage/layers-architectures#thinc-shape-inference) automatically.
> #### Example
>