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Update docs to not mention 'registration mechanism' - and move corresponding utils out of Beta #7142

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merged 6 commits into from
Feb 1, 2023
Merged

Update docs to not mention 'registration mechanism' - and move corresponding utils out of Beta #7142

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23994c2
Update docs to not mention 'registration mechanism'
NicolasHug Jan 27, 2023
6fab52e
Merge branch 'main' into docs_reg
pmeier Jan 31, 2023
212a526
Remove the .. betastatus directives
NicolasHug Feb 1, 2023
f606df8
Merge branch 'docs_reg' of github.com:NicolasHug/vision into docs_reg
NicolasHug Feb 1, 2023
3f8d800
Merge branch 'main' of github.com:pytorch/vision into docs_reg
NicolasHug Feb 1, 2023
617be1b
Merge branch 'main' into docs_reg
pmeier Feb 1, 2023
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13 changes: 7 additions & 6 deletions docs/source/models.rst
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Expand Up @@ -120,13 +120,14 @@ behavior, such as batch normalization. To switch between these modes, use
# Set model to eval mode
model.eval()

Model Registration Mechanism
----------------------------
Listing and retrieving available models
---------------------------------------

.. betastatus:: registration mechanism
.. betastatus:: these helpers
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This is rendered as

"The these helpers is in Beta stage, and backward compatibility is not guaranteed."

See

vision/docs/source/beta_status.py

Line 10 in 43df72f

text = f"The {api_name} is in Beta stage, and backward compatibility is not guaranteed."

Suggested change
.. betastatus:: these helpers
.. betastatus:: API for listing and retrieving available models

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Ah yes, thanks.
You know what, let's just remove that and make them stable. We won't be breaking them anyway so there's no reason they should be beta.


As of v0.14, TorchVision offers a new model registration mechanism which allows retreaving models
and weights by their names. Here are a few examples on how to use them:
As of v0.14, TorchVision offers a new mechanism which allows listing and
retrieving models and weights by their names. Here are a few examples on how to
use them:

.. code:: python

Expand All @@ -148,7 +149,7 @@ and weights by their names. Here are a few examples on how to use them:
weights_enum2 = get_model_weights(torchvision.models.quantization.mobilenet_v3_large)
assert weights_enum == weights_enum2

Here are the available public methods of the model registration mechanism:
Here are the available public functions to retrieve models and their corresponding weights:

.. currentmodule:: torchvision.models
.. autosummary::
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