def learn(self, BATCH: Data):
BATCH = self._preprocess_BATCH(BATCH) # [T, B, *]
for _ in range(self._epochs):
for _BATCH in BATCH.sample(self._chunk_length,
self.batch_size,
repeat=self._sample_allow_repeat):
_BATCH = self._before_train(_BATCH)
summaries = self._train(_BATCH)
self.summaries.update(summaries)
self._after_train()
def learn(self, BATCH: Data):
BATCH = self._preprocess_BATCH(BATCH) # [T, B, *]
for _ in range(self._epochs):
kls = []
for _BATCH in BATCH.sample(self._chunk_length, self.batch_size, repeat=self._sample_allow_repeat):
_BATCH = self._before_train(_BATCH)
summaries, kl = self._train(_BATCH)
kls.append(kl)
self.summaries.update(summaries)
self._after_train()
if self._use_early_stop and sum(kls) / len(kls) > self._kl_stop:
break
