def train_epoch(self, epoch_info: EpochInfo) -> None:
""" Train model for a single epoch """
epoch_info.on_epoch_begin()
for batch_idx in tqdm.trange(epoch_info.batches_per_epoch, file=sys.stdout, desc="Training", unit="batch"):
batch_info = BatchInfo(epoch_info, batch_idx)
batch_info.on_batch_begin()
self.train_batch(batch_info)
batch_info.on_batch_end()
epoch_info.result_accumulator.freeze_results()
epoch_info.on_epoch_end()
def train_epoch(self, epoch_info: EpochInfo):
""" Train model on an epoch of a fixed number of batch updates """
epoch_info.on_epoch_begin()
for batch_idx in tqdm.trange(epoch_info.batches_per_epoch,
file=sys.stdout,
desc="Training",
unit="batch"):
batch_info = BatchInfo(epoch_info, batch_idx)
batch_info.on_batch_begin()
self.train_batch(batch_info)
batch_info.on_batch_end()
epoch_info.result_accumulator.freeze_results()
epoch_info.on_epoch_end()