AdamW(fused=True) slower than unfused AdamW#121857 Open Sign up for freeto join this conversation on GitHub. Already have an account?Sign in to comment Skylion007Skylion007 left review comments janeyx99janeyx99 approved these changes mlazosAwaiting requested review from mlazos ...
case ADAM_MODE::ADAMW: param -= lr * weight_decay * param; break; if constexpr (adam_mode == ADAM_MODE::ORIGINAL) { grad += param * weight_decay; } else if constexpr (adam_mode == ADAM_MODE::ADAMW) { param -= lr * weight_decay * param; ...
实验选取的 LLaMA 模型使用 128K 个 Token 的词汇表,支持的序列长度最长为 2K。实验使用的 AdamW 优化器遵循 LLaMA 的训练设置。所有训练运行都采用bfloat16混合精度。实验使用 ZeRO-1 来做数据并行(对 Optimizer State 做分片),所使用的通信框架是torch.distributed包,其中包含NCCL。 我们对不同的分布式策略和其他...
# 需要导入模块: from apex import optimizers [as 别名]# 或者: from apex.optimizers importFusedAdam[as 别名]defoptimizer_from_name(optim_name):optim_name = optim_name.lower()ifoptim_name =="sgd":returnoptim.SGDelifoptim_name =="sgdw":returnSGDWelifoptim_name =="adam":returnpartial(optim....
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adamWflag: True, numel: 1024, num_tensors: 100 | 10 | 100 amsgrad: False, adamWflag: True, numel: 1024, num_tensors: 100 | 9 | 89 amsgrad: True, adamWflag: False, numel: 1024, num_tensors: 100 | 9 | 90 amsgrad: False, adamWflag: False, numel: 1024, num_tensors: 100 |...
🐛 Describe the bug torch._fused_adamw_( RuntimeError: params, grads, exp_avgs, and exp_avg_sqs must have same dtype, device, and layout Versions 2.2.1
/site-packages/torch/optim/adamw.py", line 615, in _fused_adamw torch._fused_adamw_( RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument state_steps in method wrapper_CUDA___fused_adamw_)...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - [MPS] Fused Adam & AdamW · pytorch/pytorch@16e1bb6
# transformers AdamW. The input arguments also have the same defaults. if amsgrad: raise RuntimeError('FusedAdam does not support the AMSGrad variant.') @@ -70,29 +74,25 @@ def __init__(self, eps=eps, weight_decay=weight_decay) super(FusedAdam, self).__init__(params, defaults) ...