[Release 0.4.0] Update DataLoader2 README and fix broken links in doc (…

…#554)

* Small README update for DataLoader2 (#541)

Summary: Pull Request resolved: #541

Test Plan: Imported from OSS

Reviewed By: ejguan

Differential Revision: D37394421

Pulled By: NivekT

fbshipit-source-id: 1fc9d47b44bc9348e3489f5e2a71a40010f527fc

* Update changed links in documentation (#543)

Summary:
Pull Request resolved: #543

Fixes #540

Test Plan: Imported from OSS

Reviewed By: ejguan

Differential Revision: D37394420

Pulled By: NivekT

fbshipit-source-id: 6a29514885d64868956fa8c24cde958db1461b6b

README.md

@@ -204,14 +204,14 @@ A: Multi-process data loading is still handled by the `DataLoader`, see the
 [DataLoader documentation for more details](https://pytorch.org/docs/stable/data.html#single-and-multi-process-data-loading).
 As of PyTorch version >= 1.12.0 (TorchData version >= 0.4.0), data sharding is automatically done for DataPipes within
 the `DataLoader` as long as a `ShardingFiler` DataPipe exists in your pipeline. Please see the
-[tutorial](https://pytorch.org/data/beta/tutorial.html#working-with-dataloader) for an example.
+[tutorial](https://pytorch.org/data/main/tutorial.html#working-with-dataloader) for an example.
 
 Q: What is the upcoming plan for DataLoader?
 
-A: There will be a new version of DataLoader in the next release. At the high level, the plan is that DataLoader V2 will
-only be responsible for multiprocessing, distributed, and similar functionalities, not data processing logic. All data
-processing features, such as the shuffling and batching, will be moved out of DataLoader to DataPipe. At the same time,
-the current/old version of DataLoader should still be available and you can use DataPipes with that as well.
+A: `DataLoader2` is in the prototype phase and more features are actively being developed. Please see the
+[README file in `torchdata/dataloader2`](https://github.com/pytorch/data/blob/main/torchdata/dataloader2/README.md). If
+you would like to experiment with it (or other prototype features), we encourage you to install the nightly version of
+this library.
 
 Q: Why is there an Error saying the specified DLL could not be found at the time of importing `portalocker`?
 

docs/source/examples.rst

@@ -56,13 +56,13 @@ Vision
 
 Caltech 101
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
-The `Caltech 101 dataset <http://www.vision.caltech.edu/Image_Datasets/Caltech101/>`_ contains pictures of objects
+The `Caltech 101 dataset <https://data.caltech.edu/records/20086>`_ contains pictures of objects
 belonging to 101 categories. Here is the
 `DataPipe implementation of Caltech 101 <https://github.com/pytorch/data/blob/main/examples/vision/caltech101.py>`_.
 
 Caltech 256
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
-The `Caltech 256 dataset <http://www.vision.caltech.edu/Image_Datasets/Caltech256/>`_ contains 30607 images
+The `Caltech 256 dataset <https://data.caltech.edu/records/20087>`_ contains 30607 images
 from 256 categories. Here is the
 `DataPipe implementation of Caltech 256 <https://github.com/pytorch/data/blob/main/examples/vision/caltech256.py>`_.
 

docs/source/tutorial.rst

@@ -171,7 +171,7 @@ Note:
   operations such as decoding, in order to avoid repeating these expensive operations across worker/distributed processes.
 
 
-You can find more DataPipe implementation examples for various research domains `on this page <torchexamples.html>`_.
+You can find more DataPipe implementation examples for various research domains `on this page <examples.html>`_.
 
 
 Implementing a Custom DataPipe

torchdata/dataloader2/README.md

@@ -82,4 +82,5 @@ A sequence of graph utilities are provided to help users to define their own `Re
 ## Prototype Usage and Feedback
 
 `DataLoader2` is stable in terms of API, but functionally not complete yet. We welcome early adopters and feedback, as
-well as potential contributors.
+well as potential contributors. If you are interested in trying it out, we encourage you to install the nightly version
+of this library.