Merge pull request #1398 from rstudio/retether-3.0.4-2

New symbols added between Keras 3.0.0 -> 3.0.4

.tether/man/activation_hard_silu.txt

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+__signature__
+keras.activations.hard_silu(x)
+__doc__
+Hard SiLU activation function, also known as Hard Swish.
+
+It is defined as:
+
+- `0` if `if x < -3`
+- `x` if `x > 3`
+- `x * (x + 3) / 6` if `-3 <= x <= 3`
+
+It's a faster, piecewise linear approximation of the silu activation.
+
+Args:
+    x: Input tensor.
+
+Reference:
+
+- [A Howard, 2019](https://arxiv.org/abs/1905.02244)
+

.tether/man/callback_swap_ema_weights.txt

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+Help on class SwapEMAWeights in module keras.src.callbacks.swap_ema_weights:
+
+class SwapEMAWeights(keras.src.callbacks.callback.Callback)
+ |  SwapEMAWeights(swap_on_epoch=False)
+ |
+ |  Swaps model weights and EMA weights before and after evaluation.
+ |
+ |  This callbacks replaces the model's weight values with the values of
+ |  the optimizer's EMA weights (the exponential moving average of the past
+ |  model weights values, implementing "Polyak averaging") before model
+ |  evaluation, and restores the previous weights after evaluation.
+ |
+ |  The `SwapEMAWeights` callback is to be used in conjunction with
+ |  an optimizer that sets `use_ema=True`.
+ |
+ |  Note that the weights are swapped in-place in order to save memory.
+ |  The behavior is undefined if you modify the EMA weights
+ |  or model weights in other callbacks.
+ |
+ |  Example:
+ |
+ |  ```python
+ |  # Remember to set `use_ema=True` in the optimizer
+ |  optimizer = SGD(use_ema=True)
+ |  model.compile(optimizer=optimizer, loss=..., metrics=...)
+ |
+ |  # Metrics will be computed with EMA weights
+ |  model.fit(X_train, Y_train, callbacks=[SwapEMAWeights()])
+ |
+ |  # If you want to save model checkpoint with EMA weights, you can set
+ |  # `swap_on_epoch=True` and place ModelCheckpoint after SwapEMAWeights.
+ |  model.fit(
+ |      X_train,
+ |      Y_train,
+ |      callbacks=[SwapEMAWeights(swap_on_epoch=True), ModelCheckpoint(...)]
+ |  )
+ |  ```
+ |
+ |  Args:
+ |      swap_on_epoch: whether to perform swapping at `on_epoch_begin()`
+ |          and `on_epoch_end()`. This is useful if you want to use
+ |          EMA weights for other callbacks such as `ModelCheckpoint`.
+ |          Defaults to `False`.
+ |
+ |  Method resolution order:
+ |      SwapEMAWeights
+ |      keras.src.callbacks.callback.Callback
+ |      builtins.object
+ |
+ |  Methods defined here:
+ |
+ |  __init__(self, swap_on_epoch=False)
+ |      Initialize self.  See help(type(self)) for accurate signature.
+ |
+ |  on_epoch_begin(
+ |    self,
+ |    epoch,
+ |    logs=None
+ |  )
+ |      Called at the start of an epoch.
+ |
+ |      Subclasses should override for any actions to run. This function should
+ |      only be called during TRAIN mode.
+ |
+ |      Args:
+ |          epoch: Integer, index of epoch.
+ |          logs: Dict. Currently no data is passed to this argument for this
+ |            method but that may change in the future.
+ |
+ |  on_epoch_end(
+ |    self,
+ |    epoch,
+ |    logs=None
+ |  )
+ |      Called at the end of an epoch.
+ |
+ |      Subclasses should override for any actions to run. This function should
+ |      only be called during TRAIN mode.
+ |
+ |      Args:
+ |          epoch: Integer, index of epoch.
+ |          logs: Dict, metric results for this training epoch, and for the
+ |            validation epoch if validation is performed. Validation result
+ |            keys are prefixed with `val_`. For training epoch, the values of
+ |            the `Model`'s metrics are returned. Example:
+ |            `{'loss': 0.2, 'accuracy': 0.7}`.
+ |
+ |  on_predict_begin(self, logs=None)
+ |      Called at the beginning of prediction.
+ |
+ |      Subclasses should override for any actions to run.
+ |
+ |      Args:
+ |          logs: Dict. Currently no data is passed to this argument for this
+ |            method but that may change in the future.
+ |
+ |  on_predict_end(self, logs=None)
+ |      Called at the end of prediction.
+ |
+ |      Subclasses should override for any actions to run.
+ |
+ |      Args:
+ |          logs: Dict. Currently no data is passed to this argument for this
+ |            method but that may change in the future.
+ |
+ |  on_test_begin(self, logs=None)
+ |      Called at the beginning of evaluation or validation.
+ |
+ |      Subclasses should override for any actions to run.
+ |
+ |      Args:
+ |          logs: Dict. Currently no data is passed to this argument for this
+ |            method but that may change in the future.
+ |
+ |  on_test_end(self, logs=None)
+ |      Called at the end of evaluation or validation.
+ |
+ |      Subclasses should override for any actions to run.
+ |
+ |      Args:
+ |          logs: Dict. Currently the output of the last call to
+ |            `on_test_batch_end()` is passed to this argument for this method
+ |            but that may change in the future.
+ |
+

.tether/man/keras.activations.txt

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+deserialize(config, custom_objects=None)
+elu(x, alpha=1.0)
+exponential(x)
+gelu(x, approximate=False)
+get(identifier)
+hard_sigmoid(x)
+hard_silu(x)
+hard_swish(x)
+leaky_relu(x, negative_slope=0.2)
+linear(x)
+log_softmax(x, axis=-1)
+mish(x)
+relu(
+  x,
+  negative_slope=0.0,
+  max_value=None,
+  threshold=0.0
+)
+relu6(x)
+selu(x)
+serialize(activation)
+sigmoid(x)
+silu(x)
+softmax(x, axis=-1)
+softplus(x)
+softsign(x)
+swish(x)
+tanh(x)
+