train_step

FullyConnected.train_step(data)

The logic for one training step.

This method can be overridden to support custom training logic. For concrete examples of how to override this method see [Customizing what happens in fit]( https://www.tensorflow.org/guide/keras/customizing_what_happens_in_fit). This method is called by Model.make_train_function.

This method should contain the mathematical logic for one step of training. This typically includes the forward pass, loss calculation, backpropagation, and metric updates.

Configuration details for how this logic is run (e.g. tf.function and tf.distribute.Strategy settings), should be left to Model.make_train_function, which can also be overridden.

Parameters:

data – A nested structure of `Tensor`s.

Returns:

A dict containing values that will be passed to tf.keras.callbacks.CallbackList.on_train_batch_end. Typically, the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.