如果确认库存在但无法导入,尝试重新安装 warmup_scheduler。打开你的命令行工具,运行以下命令来安装或更新库: bash pip install --upgrade warmup_scheduler 如果你在虚拟环境中工作,确保该环境已激活,并且使用正确的pip版本。 检查代码中是否正确导入了模块: 在你的Python代码中,确保你使用了正确的导入语句。例如...
self.after_scheduler.step(epoch - self.warmup_epoch) # 注意CosineAnnealingLR要从0epoch开始,所以需要减去 else: super(GradualWarmupScheduler, self).step(epoch) # warmup范围,使用当前重构类的() 对于超过warmup范围,直接使用CosineAnnealingLR类,比较简单 对于warmup范围类,使用当前重构类的step()函数,因为...
= ReduceLROnPlateau: if self.finished and self.after_scheduler: if epoch is None: self.after_scheduler.step(None) else: self.after_scheduler.step(epoch - self.total_epoch) else: return super(GradualWarmupScheduler, self).step(epoch) else: self.step_ReduceLROnPlateau(metrics, epoch) 1 2 3...
warmup_scheduler .gitignore LICENSE README.md setup.py pytorch-gradual-warmup-lr Gradually warm-up(increasing) learning rate for pytorch's optimizer. Proposed in 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour'. Install $ pip install git+https://github.com/ildoonet/pytorch-gradu...
Gradually warm-up(increasing) learning rate for pytorch's optimizer. Proposed in 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour'. Example : Gradual Warmup for 100 epoch, after that, use cosine-annealing. Install $ pip install git+https://github.com/ildoonet/pytorch-gradual-war...
classWarmUpCosineDecayScheduler(keras.callbacks.Callback): """Cosine decay with warmup learning rate scheduler """ def__init__(self, learning_rate_base, total_steps, global_step_init=0, warmup_learning_rate=0.0, warmup_steps=0, hold_base_rate_steps=0, ...
一、介绍GradualWarmupScheduler GradualWarmupScheduler(optimizer, multiplier, total_epoch, after_scheduler) 参数解释: optimizer:优化器 multiplier:当multiplier=1.0时,学习率lr从0开始增到base_lr为止,当multiplier大于1.0时,学习率lr从base_lr开始增到base_lr*multiplier为止。multiplier不能小于1.0。 【那么base_...
这样,我们就可以根据不同的学习率计算方式设计自己的scheduler类了。warmup初始训练阶段,直接使用较大学习率会导致权重变化较大,出现振荡现象,使得模型不稳定,加大训练难度。而使用Warmup预热学习率,在开始的几个epoch,逐步增大学习率,如下图所示,使得模型逐渐趋于稳定,等模型相对稳定后再选择预先设置的基础学习率进行...
Hello, When I try to execute the line of code below, Python gives me an import error: from pytorch_transformers import (GPT2Config, GPT2LMHeadModel, GPT2DoubleHeadsModel, AdamW, get_linear_schedule_with_warmup) ImportError: cannot import...
Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系,成为中文AIGC和认知智能的基础设施。 - FEAT:新增scheduler参数, 支持更精细的warmup配置 · Rempage/Fengshenbang-LM@c4ad096