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Modified the validate_tf_v2_checkpoint_restore_map function when the input is a recurred dictionary.

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Switching UV_symmetry_transforms.mat (for DensePose) from float64 to uint8. This bring the file size from 22MB to 3.1MB.

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Polish Seq2SeqTransformer: (1) consolidate args; (2) add tests for distribution strategy and decoding path. (3) fix bugs

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Change TF badges

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* Merged commit includes the following changes:
326369548  by Andre Araujo:

    Fix import issues.

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326159826  by Andre Araujo:

    Changed the implementation of the cosine weights from Keras layer to tf.Variable to manually control for L2 normalization.

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326139082  by Andre Araujo:

    Support local feature matching using ratio test.

    To allow for easily choosing which matching type to use, we rename a flag/argument and modify all related files to avoid breakages.

    Also include a small change when computing nearest neighbors for geometric matching, to parallelize computation, which saves a little bit of time during execution (argument "n_jobs=-1").

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326119848  by Andre Araujo:

    Option to measure DELG latency taking binarization into account.

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324316608  by Andre Araujo:

    DELG global features training.

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323693131  by Andre Araujo:

    PY3 conversion for delf public lib.

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321046157  by Andre Araujo:

    Purely Google refactor

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* Added export of delg_model module.

* README update to explain training DELG global features head
Co-authored-by: Andre Araujo <andrearaujo@google.com>

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* Added TF-Lite-compatible feature extractor and model exporter for YAMNet.

- Added a TF-Lite compatible feature extractor. With the latest TF-Lite,
  that involves a DFT-multiplication replacement for tf.abs(tf.signal.stft())
  and not a lot else. Note that TF-Lite now allows variable-length inputs.
- Added a YAMNet exporter that produces TF2 SavedModels, TF-Lite models,
  and TF-JS models.
- Cleanups: switched hyperparameters to a dataclass, got rid of
  some lingering cruft in yamnet_test.

* Responded to DAn's comments in https://github.com/tensorflow/models/pull/9098

- Switched some hparams to float
- Made class map asset available on the exported model, and tested that
  it can be loaded from the various exports.

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Testing: Trained Bert2Bert model with MLIR bridge enabled and then NHNet based on Bert2Bert checkpoint, also with MLIR bridge enabled. Exported this to a saved model, ran inference, and confirmed model performance, accuracy, and prediction parity with the model trained without the MLIR bridge enabled.
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