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  1. 15 Apr, 2021 1 commit
  3. 13 Apr, 2021 2 commits
    • A. Unique TensorFlower's avatar
      Internal change · f4bd58dd
      A. Unique TensorFlower authored 
      PiperOrigin-RevId: 368260712
      f4bd58dd
    • Reed Wanderman-Milne's avatar
      Use nonexperimental mixed precision API. · 9a4d14a9
      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
      9a4d14a9
  5. 06 Apr, 2021 1 commit
    • Jeremiah Liu's avatar
      Disable temperature scaling during training. · ff3ed4cc
      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
      ff3ed4cc
  7. 05 Apr, 2021 1 commit
    • Jeremiah Liu's avatar
      Adds `call()` method to `GaussianProcessClassificationHead`. · a35d7aaa
      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
      a35d7aaa
  9. 01 Apr, 2021 3 commits
  11. 24 Mar, 2021 1 commit
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  15. 20 Mar, 2021 1 commit
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  39. 28 Jan, 2021 1 commit