量化器是一种用于将神经网络中的参数量化为离散数值的方法,它可以将神经网络中的权重和激活值等参数转换为一组离散的数值,从而降低神经网络的计算复杂度,提高计算速度。常见的量化器包括定点量化器(Fixed-Point Quantizer)、浮点量化器(Floating-Point Quantizer)等。 描述符和量化器可以结合使用,用于对神经网络进行优化。
然后我去阅读了一下最新的onnx-simplifer,在上次的ONNX初探基础上,增加了一个递归函数fixed_point,功能就是递归执行func_a和fun_b直到模型稳定,代码如下: # 递归执行func_a和func_b直到模型稳定 def fixed_point(x: T, func_a: Callable[[T], T], func_b: Callable[[T], T]) -> T: """ Run `...
然后我去阅读了一下最新的onnx-simplifer,在上次的ONNX初探基础上,增加了一个递归函数fixed_point,功能就是递归执行func_a和fun_b直到模型稳定,代码如下: # 递归执行func_a和func_b直到模型稳定 deffixed_point(x:T,func_a:Callable[[T],T],func_b:Callable[[T],T])-...
因此,Autoformer中基于随机过程理论,提出了Auto-correlation机制来代替了Transformer中的基于point-wise的self-attention机制,实现序列级(series-wise)连接和O(LlogL)的时间复杂度,打破信息利用瓶颈。 更具体的原理就不做讲解了,网上已经有了很多类似的文章,这篇文章主要讲解代码的使用,重点是如何对作者公开的源...
Tracked Regressions NCCL init hits CUDA failure 'invalid argument' on 12.2 driver Some users with 12.2 CUDA driver (535 version) report seeing "CUDA driver error: invalid argument" during NCCL or Symmetric Memory initialization. This issue is currently under investigation, see#150852. If you use...
Bug description using self.log with torch compile results in failure. pytorch/pytorch#103621 applied to mitigate "failed to reach fixed point" error with python 3.8 Pytorch lightning 2.0.5 used for the experiment What version are you see...
PointNetfrom Charles R. Qiet al.:PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation(CVPR 2017) PointNet++from Charles from Charles R. Qiet al.:PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space ...
Encoder-Decoder architecture. Typically, a model that generates sequences will use an Encoder to encode the input into a fixed form and a Decoder to decode it, word by word, into a sequence. Attention. The use of Attention networks is widespread in deep learning, and with good reason. This...
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量化(Quantization)是解决FP32 的模型在内存带宽消耗,推理速度的主要技术之一, 其采用定点(fixed point)或者整形数据(INT8)代替FP32类型, Hardware friendly。 如何学习和掌握量化技术 模型量化涉及很多概念和算法,比如 对称量化/非对称量化, 线性量化/非线性量化 等等, 了解这些基础概念之后我们最好结合实践这样才能更...