来源：MEF-GAN: Multi-Exposure Image Fusion via Generative Adversarial Networksclass Attention(nn.Module):def __init__(self, bn=True):super(Attention, self).__init__()self.conv1 = nn.Conv2d(6, 16, kernel_

import torch.nnimport torch.optimx = torch.tensor([[1., 1., 1.], [2., 3., 1.], [3., 5., 1.], [4., 2., 1.], [5., 4., 1.]])y = torch.tensor([-10., 12., 14., 16., 18.])w = torch.zeros(3, requires_gr...

from torch import nnfrom torch import optim as optimizerimport torchfrom torch.autograd import Variableimport matplotlib.pyplot as pltimport numpy as npclass Model(nn.Module):def __init__...

import torchfrom torch.autograd import Variableimport matplotlib.pyplot as pltfrom sklearn import datasetsfrom torch import nnfrom sklearn.model_selection import train_test_splitdigits = datas...

import torchfrom torch import nnimport torch.optim as optimizerfrom torch.autograd import Variableimport matplotlib.pyplot as pltfrom sklearn.model_selection import train_test_splitfrom sklear...

github网址：https://github.com/ranran4082391/GAN

借助上采样技术解决了GAN带来的棋盘效应。

https://github.com/ranran4082391/restaurant-comments 数据集地址importpandasaspdfromdateutilimportparserfromsnownlpimportSnowNLPimportmatplotlib.pyplotaspltimportnumpyasnpdf=pd.read_excel('restaurant-commen

第一次听到“增强学习”(Reinforcement Learning)的时候，我以为只是在“深度学习”的基础上又玩儿的新花样。后来稍微了解了一下，发现其实是完全不同的概念，当然它们并非互斥，反而可以组合，于是又有了“深度增强学习”(Deep Reinforcement Learning)。目前很少有用C语言去写一个强化学习的，我认为在嵌入式以及无线传感网络中强化学习也是很有用处的，因此本小编用C语