梯度检查点(Gradient Checkpointing)在上述两种方式之间取了一个平衡,这种方法采用了一种策略选择了计算图上的一部分激活值保存下来,其余部分丢弃,这样被丢弃的那一部分激活值需要在计算梯度时重新计算。 下面这个动图展示了一种简单策略:前向传播过程中计算节点的激活值并保存,计算下一个节点完成后丢弃中间节点的激活...
梯度检查点可以通过 PreTrainedModel 实例的gradient_checkpointing_enable方法执行。 代码实现 from transformers import AutoConfig, AutoModel # https://github.com/huggingface/transformers/issues/9919 from torch.utils.checkpoint import checkpoint # initializing model model_path = "microsoft/deberta-v3-base" con...
梯度检查点可以通过 PreTrainedModel 实例的gradient_checkpointing_enable方法执行。 代码实现 fromtransformersimportAutoConfig,AutoModel# https://github.com/huggingface/transformers/issues/9919fromtorch.utils.checkpointimportcheckpoint# initializing modelmodel_path="microsoft/deberta-v3-base"config=AutoConfig.from_p...
Arthur <48595927+ArthurZucker@users.noreply.github.com> * replace it with `is_gradient_checkpointing_set` * remove default * Update src/transformers/modeling_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fixup --- Co-authored-by: Arthur <48595927+Arthur...
🚀 Feature request Currently, only Bert supports gradient checkpointing which allow the model to be fine-tuned on GPUs with small memory. It will be great to make T5 also support gradient checkpointing. Code: transformers/src/transformers...
from transformers import AutoModelForCausalLM, TraininArgumentsmodel = AutoModelForCausalLM.from_pretrained( model_id, use_cache=False, # False if gradient_checkpointing=True **default_args)model.gradient_checkpointing_enable()LoRA LoRA是微软团队开发的一种技术，用于加速大型语言模型的微调。他...
set_seed(args.seed)ifargs.gradient_checkpointing: unet.enable_gradient_checkpointing()# Use 8-bit Adam for lower memory usage or to fine-tune the model in 16GB GPUsifargs.use_8bit_adam: optimizer_class = bnb.optim.AdamW8bitelse:
A PVR function with a window size of 2 is illustrated. The first three bits are the pointer, pointing to a window in the following bits. In particular, the number given by the pointer bits in binary expansion indicates the position of...
Transformers框架中开启梯度累积非常简单,仅需在TrainingArguments内指定累积步长即可: 代码语言:javascript 复制 training_args=TrainingArguments(per_device_train_batch_size=1,gradient_accumulation_steps=4,gradient_checkpointing=True,**default_args)trainer=Trainer(model=model,args=training_args,train_dataset=ds)...
四、gradient checkpointing显存优化 神经网络如何使用内存 梯度检查点是如何起作用的 五、chunk_size_applying(按多个小批量和低维度计算 FFN 部) 本章内容分四个部分讲,fp16、apm以及pytorch的多gpu训练模式、gradient checkpointing显存优化。本节内容基于pytorch==1.2.0,transformers==3.0.2python==3.6pytorch 1.6...