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hub / github.com/Monalissaa/DisenDiff / training_step

Method training_step

src/model.py:559–581  ·  view source on GitHub ↗
(self, batch, batch_idx)

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557 return out
558
559 def training_step(self, batch, batch_idx):
560 if self.controller is not None:
561 self.controller.between_steps()
562 if isinstance(batch, list):
563 train_batch = batch[0]
564 train2_batch = batch[1]
565 loss_train, loss_dict = self.shared_step(train_batch)
566 loss_train2, _ = self.shared_step(train2_batch)
567 loss = loss_train + loss_train2
568 else:
569 train_batch = batch
570 loss, loss_dict = self.shared_step(train_batch)
571
572 self.log_dict(loss_dict, prog_bar=True,
573 logger=True, on_step=True, on_epoch=True)
574
575 self.log("global_step", self.global_step,
576 prog_bar=True, logger=True, on_step=True, on_epoch=False)
577
578 if self.use_scheduler:
579 lr = self.optimizers().param_groups[0]['lr']
580 self.log('lr_abs', lr, prog_bar=True, logger=True, on_step=True, on_epoch=False)
581 return loss
582
583 def shared_step(self, batch, **kwargs):
584 x, c, mask = self.get_input_withmask(batch, **kwargs)

Callers

nothing calls this directly

Calls 2

shared_stepMethod · 0.95
between_stepsMethod · 0.45

Tested by

no test coverage detected