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  1. 15 Apr, 2021 1 commit
  3. 13 Apr, 2021 2 commits
    • A. Unique TensorFlower's avatar
      Internal change · b1aa44d9
      A. Unique TensorFlower authored 
      PiperOrigin-RevId: 368260712
      b1aa44d9
    • Reed Wanderman-Milne's avatar
      Use nonexperimental mixed precision API. · 4334a892
      Reed Wanderman-Milne authored 
      This replaces symbols in tf.keras.mixed_precision.experimental with the corresponding nonexperimental symbols. In some cases, passing a Policy is replaced with passing a policy name for conciseness.

Additionally, for the Shakespeare model, the loss_scale flag is removed, since supporting it with the nonexperimental API is slightly more verbose and it is recommended users use the default loss scale.

PiperOrigin-RevId: 368123944
      4334a892
  5. 06 Apr, 2021 1 commit
    • Jeremiah Liu's avatar
      Disable temperature scaling during training. · fab47e9e
      Jeremiah Liu authored 
      For the `GaussianProcessClassificationHead`, the temperature scaling needs to be disabled during training to avoid unexpected modification to the learning rate, which harms model quality. (Unfortunately, this seems to require adding `training` to the `call` method).

Also set the default of `gp_cov_ridge_penalty` in `RandomFeatureGaussianProcess` to 1 to be consistent with that in the `GaussianProcessClassificationHead`.

PiperOrigin-RevId: 366917075
      fab47e9e
  7. 05 Apr, 2021 1 commit
    • Jeremiah Liu's avatar
      Adds `call()` method to `GaussianProcessClassificationHead`. · 2ae06c8a
      Jeremiah Liu authored 
      This change allows `GaussianProcessClassificationHead` to output only the predictive logits during training and evaluation (instead of outputting a tuple  `(logits, covmat)`). The goal is to make the layer more compatible with `SentencePredictionTask` and Keras' `model.fit()` API.

PiperOrigin-RevId: 366891298
      2ae06c8a
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