Purge old pytorch image example and add cv guide to example gallery (r…

…ay-project#37673) Cleaning out low quality or out of date examples because we have too many. cc: @pcmoritz @peytondmurray @peytondmurray, some follow-up is needed to put the relevant tags on the new CV User Guide. --------- Signed-off-by: angelinalg <122562471+angelinalg@users.noreply.github.com>
harborn · Aug 17, 2023 · 8a564ca · 8a564ca
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diff --git a/doc/source/_toc.yml b/doc/source/_toc.yml
@@ -57,7 +57,6 @@ parts:
               - file: ray-air/deployment
           - file: ray-air/examples/index
             sections:
-              - file: ray-air/examples/torch_image_example
               - file: ray-air/examples/torch_detection
               - file: ray-air/examples/convert_existing_pytorch_code_to_ray_air
               - file: ray-air/examples/convert_existing_tf_code_to_ray_air

diff --git a/doc/source/ray-air/computer-vision.rst b/doc/source/ray-air/computer-vision.rst
@@ -183,7 +183,7 @@ Training vision models
             :end-before: __torch_trainer_stop__
             :dedent:
 
-        For more in-depth examples, read :doc:`/ray-air/examples/torch_image_example` and
+        For more in-depth examples, see
         :ref:`Using Trainers <air-trainers>`.
 
     .. tab-item:: TensorFlow
@@ -315,8 +315,7 @@ To NumPy ndarrays like this:
             :end-before: __torch_online_predict_stop__
             :dedent:
 
-        For more in-depth examples, read :doc:`/ray-air/examples/torch_image_example`
-        and :doc:`/ray-air/examples/serving_guide`.
+        For more in-depth examples, see :doc:`/ray-air/examples/serving_guide`.
 
     .. tab-item:: TensorFlow
 

diff --git a/doc/source/ray-air/examples/convert_existing_pytorch_code_to_ray_air.ipynb b/doc/source/ray-air/examples/convert_existing_pytorch_code_to_ray_air.ipynb
@@ -70,7 +70,7 @@
    "source": [
     "Then we download the data: \n",
     "\n",
-    "This tutorial assumes that your existing code is using the `torch.utils.data.Dataset` native to PyTorch. It continues to use `torch.utils.data.Dataset` to allow you to make as few code changes as possible. **This tutorial also runs with Ray Data, which gives you the benefits of efficient parallel preprocessing.** See an example of using Ray Data for the CIFAR-10 dataset {doc}`here </ray-air/examples/torch_image_example>`."
+    "This tutorial assumes that your existing code is using the `torch.utils.data.Dataset` native to PyTorch. It continues to use `torch.utils.data.Dataset` to allow you to make as few code changes as possible. **This tutorial also runs with Ray Data, which gives you the benefits of efficient parallel preprocessing.** For examples of using Ray Data for computer vision, see {doc}`Computer Vision </ray-air/computer-vision>`."
    ]
   },
   {

diff --git a/doc/source/ray-air/examples/index.rst b/doc/source/ray-air/examples/index.rst
@@ -33,7 +33,7 @@ Text/NLP
 Image/CV
 --------
 
-- :doc:`/ray-air/examples/torch_image_example`
+- :doc:`/ray-air/computer-vision`
 - :doc:`/ray-air/examples/torch_detection`
 - :doc:`/ray-air/examples/stablediffusion_batch_prediction`: How to use Ray AIR to do batch prediction with the Stable Diffusion text-to-image model.