在了解了Normalizing Flow和Glow模型的基础知识后,我们将介绍如何使用PyTorch实现该模型,并在MNIST数据集上进行训练。 Glow模型 首先,我们将使用PyTorch和nflows实现Glow架构。为了节省时间,我们使用nflows包含所有层的实现。 import torch import torch.nn as nn import torch.nn.functional as F from nflows import t...
在了解了Normalizing Flow和Glow模型的基础知识后,我们将介绍如何使用PyTorch实现该模型,并在MNIST数据集上进行训练。 Glow模型 首先,我们将使用PyTorch和nflows实现Glow架构。为了节省时间,我们使用nflows包含所有层的实现。 importtorchimporttorch.nnasnnimporttorch.nn.functionalasFfromnflowsimporttransformsimportnumpyasn...
Real NVP Flows 很容易训练，因为损失函数只需要logp(f(x))，这在 pytorch 中很容易计算，而 Jacoba...
normflows: A PyTorch Package for Normalizing Flowsnormflows is a PyTorch implementation of discrete normalizing flows. Many popular flow architectures are implemented, see the list below. The package can be easily installed via pip. The basic usage is described here, and a full documentation is av...
JingyunLiang/HCFlow Star191 Code Issues Pull requests Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) flowsuper-resolutionimage-super-resolutionnormalizing-flowiccv2021image-rescalingface-image-super-resolutionimag...
pytorch版本的，能运行就好，不论效果如何 发自小木虫Android客户端
希望是pytorch，而不是ts 发自小木虫Android客户端
All the models were implemented on PyTorch using two NVIDIA RTX A6000 GPU cards. Harmonizer. The utilized UNet network as harmonizer consists of five different scales with a scaling factor of 2, where each scale includes a layer of the modified ELU activation function, i.e., concat[ELU(x),...
Masked Autoregressive Flow for Density Estimation, NeurIPS, 2017 5.2 参考代码: https://github.com/simonwestber https://github.com/S-razmi/Real_NVP/blob/main/RealNVP.ipynb https://github.com/rosinality/glow-pytorch github.com/kamenbliznas...
sum(log_prob, dim=1) #按列求和 loss = loss_s + loss_prob #总损失 #由于pytorch是最小值优化,故取反 return -loss def generate(self,h): ''' @param h: logistic分布采样所得 @return: ''' z,s=self.scale(h,True) for i in reversed(self.couping): z=i(z,True) return z def ...