train_one_epoch函数 train_one_epoch函数是一个用于训练神经网络的函数,其主要作用是在每个epoch(迭代周期)中更新网络的权重,以逐步优化网络的性能。 该函数通常包括以下步骤: 1.将训练数据输入到网络中,并计算每个样本的输出结果。 2.根据输出结果和真实标签之间的差异,计算损失函数的值。 3.使用反向传播算法,...
def train_one_epoch(self): sum_loss = 0.0 batches = self.batch_iter() batch_id = 0 for batch in batches: h, t, sign = batch feed_dict = { self.h: h, self.t: t, self.sign: sign, } _, cur_loss = self.sess.run([self.train_op, self.loss], feed_dict) sum_loss += ...
ValueError: classEpochBasedTrainLoopin mmengine/runner/loops.py: classCocoDatasetin mmdet/datasets/coco.py: need at least one array to concatenate A placeholder for trackback. Bug fix If you have already identified the reason, you can provide the information here. If you are willing to create ...
ValueError: classEpochBasedTrainLoopin mmengine/runner/loops.py: classCocoDatasetin mmdet/datasets/coco.py: need at least one array to concatenate Additional information I ran this tutorial (https://github.com/open-mmlab/mmdetection/blob/3.x/demo/MMDet_InstanceSeg_Tutorial.ipynb) without changing ...
train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=10, val_interval=1,scope='mmdet') val_cfg = dict(type='ValLoop',scope='mmdet') test_cfg = dict(type='TestLoop',scope='mmdet') param_scheduler = [ dict(type='LinearLR', start_factor=0.1, by_epoch=False, begin=0, end=...