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Merge pull request #4364 from Matt-Hurd:matthurd/update_orbax_links
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docs/guides/converting_and_upgrading/orbax_upgrade_guide.rst

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@@ -11,7 +11,7 @@ You will learn how to migrate to Orbax through the following scenarios:
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* Async checkpointing
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* Saving/loading a single JAX or NumPy Array
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To learn more about Orbax, check out the `quick start introductory Colab notebook <http://colab.research.google.com/github/google/orbax/blob/main/checkpoint/orbax//checkpoint/orbax_checkpoint.ipynb>`__ and `the official Orbax documentation <https://github.com/google/orbax/blob/main/docs/checkpoint.md>`_.
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To learn more about Orbax, check out the `quick start introductory Colab notebook <http://colab.research.google.com/github/google/orbax/blob/main/docs/guides/checkpoint/orbax_checkpoint_101.ipynb>`__ and `the official Orbax documentation <https://orbax.readthedocs.io/en/latest/>`_.
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You can click on "Open in Colab" above to run the code from this guide.
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docs/guides/training_techniques/use_checkpointing.ipynb

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"\n",
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"For backward-compatibility, this guide shows the Orbax-equivalent calls in the Flax legacy `flax.training.checkpoints` API.\n",
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"\n",
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"If you need to learn more about `orbax.checkpoint`, refer to the [Orbax docs](https://github.com/google/orbax/blob/main/docs/checkpoint.md).\n"
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"If you need to learn more about `orbax.checkpoint`, refer to the [Orbax docs](https://orbax.readthedocs.io/en/latest/).\n"
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},
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{
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"source": [
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"Next, to use versioning and automatic bookkeeping features, you need to wrap `orbax.checkpoint.CheckpointManager` over `orbax.checkpoint.PyTreeCheckpointer`.\n",
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"\n",
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"In addition, provide `orbax.checkpoint.CheckpointManagerOptions` that customizes your needs, such as how often and on what criteria you prefer old checkpoints be deleted. See [documentation](https://github.com/google/orbax/blob/main/docs/checkpoint.md#checkpointmanager) for a full list of options offered.\n",
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"In addition, provide `orbax.checkpoint.CheckpointManagerOptions` that customizes your needs, such as how often and on what criteria you prefer old checkpoints be deleted. See [documentation](https://orbax.readthedocs.io/en/latest/guides/checkpoint/api_refactor.html) for a full list of options offered.\n",
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"\n",
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"`orbax.checkpoint.CheckpointManager` should be placed at the top-level outside your training steps to manage your saves."
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"\n",
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"On the other hand, if the reference object contains a value that is not available in the checkpoint, the checkpointing code will by default warn that some data is not compatible.\n",
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"\n",
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"To bypass the error, you need to pass an Orbax [`transform`](https://github.com/google/orbax/blob/main/docs/checkpoint.md#transformations) that teaches Orbax how to conform this checkpoint into the structure of the `custom_target`.\n",
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"To bypass the error, you need to pass an Orbax [`transform`](https://orbax.readthedocs.io/en/latest/guides/checkpoint/transformations.html) that teaches Orbax how to conform this checkpoint into the structure of the `custom_target`.\n",
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"\n",
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"In this case, pass a default `{}` that lets Orbax use values in the `custom_target` to fill in the blank. This allows you to restore an old checkpoint into a new data structure, the `CustomTrainState`."
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"##### With the legacy API\n",
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"\n",
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"Using the legacy `flax.training.checkpoints` API, similar things are doable too, but they are not as flexible as the [Orbax Transformations](https://github.com/google/orbax/blob/main/docs/checkpoint.md#transformations).\n",
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"Using the legacy `flax.training.checkpoints` API, similar things are doable too, but they are not as flexible as the [Orbax Transformations](https://orbax.readthedocs.io/en/latest/guides/checkpoint/transformations.html).\n",
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"\n",
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"You need to restore the checkpoint to a raw dict with `target=None`, modify the structure accordingly, and then deserialize it back to the original target."
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docs/guides/training_techniques/use_checkpointing.md

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For backward-compatibility, this guide shows the Orbax-equivalent calls in the Flax legacy `flax.training.checkpoints` API.
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If you need to learn more about `orbax.checkpoint`, refer to the [Orbax docs](https://github.com/google/orbax/blob/main/docs/checkpoint.md).
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If you need to learn more about `orbax.checkpoint`, refer to the [Orbax docs](https://orbax.readthedocs.io/en/latest/).
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Next, to use versioning and automatic bookkeeping features, you need to wrap `orbax.checkpoint.CheckpointManager` over `orbax.checkpoint.PyTreeCheckpointer`.
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In addition, provide `orbax.checkpoint.CheckpointManagerOptions` that customizes your needs, such as how often and on what criteria you prefer old checkpoints be deleted. See [documentation](https://github.com/google/orbax/blob/main/docs/checkpoint.md#checkpointmanager) for a full list of options offered.
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In addition, provide `orbax.checkpoint.CheckpointManagerOptions` that customizes your needs, such as how often and on what criteria you prefer old checkpoints be deleted. See [documentation](https://orbax.readthedocs.io/en/latest/guides/checkpoint/api_refactor.html) for a full list of options offered.
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`orbax.checkpoint.CheckpointManager` should be placed at the top-level outside your training steps to manage your saves.
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On the other hand, if the reference object contains a value that is not available in the checkpoint, the checkpointing code will by default warn that some data is not compatible.
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To bypass the error, you need to pass an Orbax [`transform`](https://github.com/google/orbax/blob/main/docs/checkpoint.md#transformations) that teaches Orbax how to conform this checkpoint into the structure of the `custom_target`.
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To bypass the error, you need to pass an Orbax [`transform`](https://orbax.readthedocs.io/en/latest/guides/checkpoint/transformations.html) that teaches Orbax how to conform this checkpoint into the structure of the `custom_target`.
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In this case, pass a default `{}` that lets Orbax use values in the `custom_target` to fill in the blank. This allows you to restore an old checkpoint into a new data structure, the `CustomTrainState`.
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##### With the legacy API
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Using the legacy `flax.training.checkpoints` API, similar things are doable too, but they are not as flexible as the [Orbax Transformations](https://github.com/google/orbax/blob/main/docs/checkpoint.md#transformations).
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Using the legacy `flax.training.checkpoints` API, similar things are doable too, but they are not as flexible as the [Orbax Transformations](https://orbax.readthedocs.io/en/latest/guides/checkpoint/transformations.html).
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You need to restore the checkpoint to a raw dict with `target=None`, modify the structure accordingly, and then deserialize it back to the original target.
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