样例代码 #from vector_quantize_pytorch import kmeansimporttorchimporttorch.nn.functionalasFimportnumpyasnp# A no-operation function that does nothingdefnoop(*args,**kwargs):pass# Function to normalize a tensor using L2 normalizationdefl2norm(t,dim=-1,eps=1e-6):returnF.normalize(t,p=2,dim=...
VectorQuantize是将每一个vector与内部的codebook做计算,然后得出一个quantized vector 下面是一个例子,可以通过debug来看一下内部具体的流程。下面的内容,也是根据debug走读代码分析而来。 importvector_quantize_pytorchasvqimporttorcha=torch.FloatTensor([-0.1,0.5,0.2,0.33,-0.6,0.2]).view(1,3,2)print('a=',...
从上面的例子中可以清晰地看出来,vector插入10个元素之后,capacity()函数返回13,当插入第14个元素时,begin()所代表的内存位置发生了变化。 回到“如果超过了capacity()的数量时,vector就有必要重新配置内部存储器。” vector的容量之所以很重要,有一下两个原因 一旦重新分配内存,与vector相关的所有references, pointers...
import torch from vector_quantize_pytorch import ResidualVQ residual_vq = ResidualVQ( dim = 256, codebook_size = 256, num_quantizers = 4, kmeans_init = True, # set to True kmeans_iters = 10 # number of kmeans iterations to calculate the centroids for the codebook on init ) x = to...
首先,确保你已经在你的Python环境中安装了 vector_quantize_pytorch 模块。可以通过在命令行或终端中运行以下命令来检查: bash pip show vector_quantize_pytorch 如果这个命令返回了模块的信息,说明已经安装;如果没有任何输出,说明模块尚未安装。 使用pip 进行安装: 如果模块未安装,可以通过 pip 来安装它。打开命令...
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vector-quantize-pytorch lucidrains Fetched on 2025/01/09 06:29 lucidrains/vector-quantize-pytorch Vector (and Scalar) Quantization, in Pytorch -View it on GitHub Star 2795 Rank 12344
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from vector_quantize_pytorch import LFQ # you can specify either dim or codebook_size @@ -212,7 +216,8 @@ def test_lfq(spherical): dim = 16, # this is the input feature dimension, defaults to log2(codebook_size) if not defined entropy_loss_weight = 0.1, # how much weight ...
8 changes: 4 additions & 4 deletions 8 vector_quantize_pytorch/lookup_free_quantization.py Original file line numberDiff line numberDiff line change @@ -291,6 +291,10 @@ def forward( codebook_value = torch.ones_like(x) * self.codebook_scale...