tabensemb.model.AbstractNN.training_epoch_end#
method
- AbstractNN.training_epoch_end(outputs: List[Tensor | Dict[str, Any]]) None#
Called at the end of the training epoch with the outputs of all training steps. Use this in case you need to do something with all the outputs returned by
training_step().# the pseudocode for these calls train_outs = [] for train_batch in train_data: out = training_step(train_batch) train_outs.append(out) training_epoch_end(train_outs)
- Parameters:
outputs¶ – List of outputs you defined in
training_step(). If there are multiple optimizers or when usingtruncated_bptt_steps > 0, the lists have the dimensions (n_batches, tbptt_steps, n_optimizers). Dimensions of length 1 are squeezed.- Returns:
None
Note
If this method is not overridden, this won’t be called.
def training_epoch_end(self, training_step_outputs): # do something with all training_step outputs for out in training_step_outputs: ...