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DCRNN
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logging and refactor

This commit is contained in:
Chintan Shah 2019-10-06 14:40:53 -04:00
parent 02c4681ad9
commit 55a087ac9f
1 changed files with 2 additions and 2 deletions
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model/pytorch/dcrnn_supervisor.py
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@ -155,9 +155,9 @@ class DCRNNSupervisor:
torch.nn.utils.clip_grad_norm_(self.dcrnn_model.parameters(), self.max_grad_norm) torch.nn.utils.clip_grad_norm_(self.dcrnn_model.parameters(), self.max_grad_norm)
optimizer.step() optimizer.step()
self._logger.info("epoch complete")
lr_scheduler.step() lr_scheduler.step()
self._logger.info("evaluating now!")
val_loss = self.evaluate(dataset='val') val_loss = self.evaluate(dataset='val')
end_time = time.time() end_time = time.time()
if epoch_num % log_every == 0: if epoch_num % log_every == 0: