def train(self):
for epoch in range(self.start_epoch, self.epochs + 1):
print(f"============== {epoch} epoch ==============")
print("[0 seconds] Begin training...")
timer = ExecutionTime()
self._set_model_to_train_mode()
self._train_epoch(epoch)
if self.save_checkpoint_interval != 0 and epoch % self.save_checkpoint_interval == 0:
print(
f"[{timer.duration()} seconds] Training is over, Saving..."
)
self._save_checkpoint(epoch)
if self.validation_interval != 0 and epoch % self.validation_interval == 0:
print(
f"[{timer.duration()} seconds] Validation is in progress..."
)
self._set_model_to_eval_mode()
score = self._validation_epoch(epoch)
if self._is_best_score(score, find_max=self.find_max):
self._save_checkpoint(epoch, is_best=True)
print(f"[{timer.duration()} seconds] End this epoch.")
def train(self):
for epoch in range(self.start_epoch, self.epochs + 1):
print(f"============ Train epoch = {epoch} ============")
print("[0 seconds] 开始训练...")
timer = ExecutionTime()
self.viz.set_epoch(epoch)
self._train_epoch(epoch)
if epoch % self.save_period == 0:
self._save_checkpoint(epoch)
if self.validation_period != 0 and epoch % self.validation_period == 0:
# 测试一轮，并绘制波形文件
print(f"[{timer.duration()} seconds] 训练结束，开始计算评价指标...")
score = self._valid_epoch(epoch)
if self._is_best_score(score):
self._save_checkpoint(epoch, is_best=True)
print(f"[{timer.duration()} seconds] 完成当前 Epoch.")