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Add TextCatReduce.v1 #13181

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merged 14 commits into from
Dec 21, 2023
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danieldk
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@danieldk danieldk commented Dec 5, 2023

Description

This is a textcat classifier that pools the vectors generated by a tok2vec implementation and then applies a classifier to the pooled representation. Three reductions are supported for pooling: first, max, and mean. When multiple reductions are enabled, the reductions are concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only supports mean reductions and is a bit of a misnomer, because it can also be used with transformers. This change also reimplements TextCatCNN.v2 using the new TextCatReduce.v1 layer.

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

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  • I confirm that I have the right to submit this contribution under the project's MIT license.
  • I ran the tests, and all new and existing tests passed.
  • My changes don't require a change to the documentation, or if they do, I've added all required information.

@danieldk danieldk added enhancement Feature requests and improvements feat / textcat Feature: Text Classifier labels Dec 5, 2023
This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.
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@svlandeg svlandeg left a comment

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Nice!

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

The docs can be moved to legacy, and the code can go into spacy-legacy, but all existing code should ideally just continue to work as-is. Why wouldn't/couldn't it?

https://spacy.io/api/architectures#TextCatCNN could just refer to the legacy docs and/or the new TextCatReduce.

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danieldk commented Dec 7, 2023

Nice!

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

The docs can be moved to legacy, and the code can go into spacy-legacy, but all existing code should ideally just continue to work as-is. Why wouldn't/couldn't it?

I just noticed that there is a word missing in my initial comment:

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN (documentation) anchor does not work anymore and there may be existing pages and tutorials linking to that.

Currently, pages can link to https://spacy.io/api/architectures#TextCatCNN

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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svlandeg commented Dec 7, 2023

Currently, pages can link to https://spacy.io/api/architectures#TextCatCNN

Right - yes it dawned on me what you meant after writing the comment. We could just have a short dummy section, forwarding to the correct place.

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One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

I think you can add a redirect to netlify.toml to handle that kind of change.

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danieldk commented Dec 8, 2023

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

I think you can add a redirect to netlify.toml to handle that kind of change.

Cool, works with anchors too 🙏 .

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danieldk commented Dec 8, 2023

One thing I wasn't certain of is what to do with the TextCatCNN.v2 docs. We could move them to legacy, however, this would mean that the existing TextCatCNN does not work anymore and there may be existing pages and tutorials linking to that.

I think you can add a redirect to netlify.toml to handle that kind of change.

Cool, works with anchors too 🙏 .

Or at least I got that impression from the existing rule files. But it doesn't seem to actually work, e.g. the existing rule for

https://spacy.io/api#cython

does not seem to cause a redirection to

https://spacy.io/api/cython

?

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@adrianeboyd adrianeboyd merged commit 7ebba86 into explosion:master Dec 21, 2023
13 checks passed
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request Mar 14, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request Mar 29, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request Apr 17, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request Apr 17, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 10, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 10, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 10, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 10, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
jordankanter pushed a commit to jordankanter/spaCy that referenced this pull request May 21, 2024
* Add TextCatReduce.v1

This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.

This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.

* Doc fixes

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence

* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy

* Add back a test for TextCatCNN.v2

* Replace TextCatCNN in pipe configurations and templates

* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor

* Add last reduction (`use_reduce_last`)

* Remove non-working TextCatCNN Netlify redirect

* Revert layer changes for the quickstart

* Revert one more quickstart change

* Remove unused import

* Fix docstring

* Fix setting name in error message

---------

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
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enhancement Feature requests and improvements feat / textcat Feature: Text Classifier
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3 participants