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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`.

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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.

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both are tracked in the same bug.

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convert Dimension to int to avoid "TypeError: unsupported operand type(s) for /: float and Dimension"

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Add back-ticks around code in the docs of nlp modeling library, so that the name will get auto-linked to that api page.

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what https://github.com/tensorflow/tensorflow/issues/46293 reported at first.

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reported in https://github.com/tensorflow/tensorflow/issues/46293.

A test case is added to export_tfhub_lib_test.

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Remember the input shapes when build_from_signature is called and trigger the build in from_config.

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Ask users to use keras_nlp.

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