量化的前馈推导加入量化模拟,实际上量化的输入和输出都是浮点,具体可以参考 Quantization - PyTorch 1.13 documentation,因此做的是全浮点的反向传播,只是这个过程中多了一些因为量化引入的其他反向传播操作。 另外,Google 最新的研究是直接用定点做前馈和反向求导,但是目前还没有开放。 2023-03-08
PyTorch最近一年发布了一些生成式AI模型的案例研究,这些模型运行速度极快,且代码及其精简。这些模型比如GPT-FAST,SAM-FAST都应用了量化技术,Charles很大程度上是这些量化Kernel的主要开发者。因此,这节课由Charles来分享量化技术。
int4[2*k,n]=(uint4x2[k,n] & 0xF) - 8 int4[2*k+1,n]=(uint4x2[k,n] >> 4) - 8 解释说选择uint8是因为triton框架对int8的位移操作存在问题。这里的uint4x2量化Kernel代码在:github.com/pytorch/pyto 这张Slides主要讨论了Int4权重量化(Int4 Weight Only Quantization)的性能表现和一些相关观...
bitsandbytes Test cleanup (#1576) Mar 28, 2025 csrc PyTorch Custom Operator Integration (#1544) Mar 26, 2025 docs/source PyTorch Custom Operator Integration (#1544) Mar 26, 2025 examples Drop Python 3.8 support. (#1574) Mar 28, 2025 ...
Your current environment $ python collect_env.py Collecting environment information... PyTorch version: 2.3.0+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A OS: Ubuntu 22.04.4 LTS (x86_64) GC...
In quantized networks, the number of bits used to represent numbers defining a model is reduced. This provides a decrease of orders of magnitude in computing, memory and power requirements, for a comparatively low decrease in performance. Quantization may be applied to weights, activation functions...
Armed with this understanding, we design a method that quantizes the layer parameters jointly, enabling significant accuracy improvement over current post-training quantization methods. Reference implementation is available at https://github.com/ynahshan/nn-quantization-pytorch/tree/master/lapq....
https://github.com/openvinotoolkit/openvino/blob/master/tools/pot/configs/examples/quantization/optimization/mobilenetV2_pytorch_int8_rangeopt.json { "name": "MinMaxQuantization", "params": { "preset": "mixed", "stat_sub...
2.3 How Many Bits do We Need? image.png 2.4 Summary 计算图如下 image.png 在执行推理时,利用查找表将权重压缩 K-Means量化只节约了模型的存储开销 所有的计算和内存访问依然是浮点数 image.png Linear Quantization不仅用Integer来存储,也用Interger来计算 ...
Your current environment PyTorch version: 2.4.0+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A OS: Ubuntu 22.04.5 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version...