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Jun 4, 2025
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Update broken links tia index 3372 #3376

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15314bb
Fix broken links in intermediate_source/tiatoolbox_tutorial.rst
nirajkamal Jun 3, 2025
d8fcaf9
Update broken links in index.rst
nirajkamal Jun 3, 2025
9f9262b
Fix index.rst ios executorch demo link
nirajkamal Jun 3, 2025
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12 changes: 6 additions & 6 deletions index.rst
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Expand Up @@ -806,21 +806,21 @@ Welcome to PyTorch Tutorials
:header: Using the ExecuTorch SDK to Profile a Model
:card_description: Explore how to use the ExecuTorch SDK to profile, debug, and visualize ExecuTorch models
:image: _static/img/ExecuTorch-Logo-cropped.svg
:link: https://pytorch.org/executorch/stable/tutorials/sdk-integration-tutorial.html
:link: https://docs.pytorch.org/executorch/main/tutorials/devtools-integration-tutorial.html
:tags: Edge

.. customcarditem::
:header: Building an ExecuTorch iOS Demo App
:card_description: Explore how to set up the ExecuTorch iOS Demo App, which uses the MobileNet v3 model to process live camera images leveraging three different backends: XNNPACK, Core ML, and Metal Performance Shaders (MPS).
:image: _static/img/ExecuTorch-Logo-cropped.svg
:link: https://pytorch.org/executorch/stable/demo-apps-ios.html
:link: https://github.com/pytorch-labs/executorch-examples/tree/main/mv3/apple/ExecuTorchDemo
:tags: Edge

.. customcarditem::
:header: Building an ExecuTorch Android Demo App
:card_description: Learn how to set up the ExecuTorch Android Demo App for image segmentation tasks using the DeepLab v3 model and XNNPACK FP32 backend.
:image: _static/img/ExecuTorch-Logo-cropped.svg
:link: https://pytorch.org/executorch/stable/demo-apps-android.html
:link: https://github.com/pytorch-labs/executorch-examples/tree/main/dl3/android/DeepLabV3Demo#executorch-android-demo-app
:tags: Edge

.. customcarditem::
Expand Down Expand Up @@ -1123,9 +1123,9 @@ Additional Resources

Exporting to ExecuTorch Tutorial <https://pytorch.org/executorch/stable/tutorials/export-to-executorch-tutorial.html>
Running an ExecuTorch Model in C++ Tutorial < https://pytorch.org/executorch/stable/running-a-model-cpp-tutorial.html>
Using the ExecuTorch SDK to Profile a Model <https://pytorch.org/executorch/stable/tutorials/sdk-integration-tutorial.html>
Building an ExecuTorch iOS Demo App <https://pytorch.org/executorch/stable/demo-apps-ios.html>
Building an ExecuTorch Android Demo App <https://pytorch.org/executorch/stable/demo-apps-android.html>
Using the ExecuTorch SDK to Profile a Model <https://docs.pytorch.org/executorch/main/tutorials/devtools-integration-tutorial.html>
Building an ExecuTorch iOS Demo App <https://github.com/pytorch-labs/executorch-examples/tree/main/mv3/apple/ExecuTorchDemo>
Building an ExecuTorch Android Demo App <https://github.com/pytorch-labs/executorch-examples/tree/main/dl3/android/DeepLabV3Demo#executorch-android-demo-app>
Lowering a Model as a Delegate <https://pytorch.org/executorch/stable/examples-end-to-end-to-lower-model-to-delegate.html>

.. toctree::
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4 changes: 2 additions & 2 deletions intermediate_source/tiatoolbox_tutorial.rst
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Expand Up @@ -348,7 +348,7 @@ The PatchPredictor class runs a CNN-based classifier written in PyTorch.
- Alternatively, you can pass ``pretrained_model`` as a string
argument. This specifies the CNN model that performs the prediction,
and it must be one of the models listed
`here <https://tia-toolbox.readthedocs.io/en/latest/usage.html?highlight=pretrained%20models#tiatoolbox.models.architecture.get_pretrained_model>`__.
`here <https://tia-toolbox.readthedocs.io/en/stable/_autosummary/tiatoolbox.models.architecture.get_pretrained_model.html#tiatoolbox.models.architecture.get_pretrained_model>`__.
The command will look like this:
``predictor = PatchPredictor(pretrained_model='resnet18-kather100k', pretrained_weights=weights_path, batch_size=32)``.
- ``pretrained_weights``: When using a ``pretrained_model``, the
Expand Down Expand Up @@ -621,7 +621,7 @@ results. Here are the arguments and their descriptions:
which is equivalent to level 0. In general, this is the level of
greatest resolution. In this particular case, the image has only one
level. More information can be found in the
`documentation <https://tia-toolbox.readthedocs.io/en/latest/usage.html?highlight=WSIReader.read_rect#tiatoolbox.wsicore.wsireader.WSIReader.read_rect>`__.
`documentation <https://tia-toolbox.readthedocs.io/en/stable/_autosummary/tiatoolbox.wsicore.wsireader.WSIReader.html#tiatoolbox.wsicore.wsireader.WSIReader.read_rect>`__.
- ``masks``: A list of paths corresponding to the masks of WSIs in the
``imgs`` list. These masks specify the regions in the original WSIs
from which we want to extract patches. If the mask of a particular
Expand Down