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RSS订阅原创 BRAT 部署学习记录，及问题解决
find txtann（文件夹） -name ‘*.txt’|sed -e ‘s|.txt|.ann|g’|xargs touch。
2023-09-21 17:16:34
162
原创 异或门（完整）
import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)orgate = torch.tensor([0,1,1,1],dtype = torch.float32)def OR(X): w = torch.tensor([-0.5,1,1] ,dtype = torch.float32) # b,w1,w2 zhat = torch.mv(X,w) yha.
2021-02-03 17:36:10
2387
原创 异或门
import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)orgate = torch.tensor([0,1,1,1],dtype = torch.float32)def OR(X): w = torch.tensor([-0.5,1,1] ,dtype = torch.float32) # b,w1,w2 zhat = torch.mv(X,w) yhat
2021-02-03 17:19:51
516
原创 或门
import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)orgate = torch.tensor([[0],[1],[1],[1]],dtype = torch.float32)w = torch.tensor([-0.5,1,1] ,dtype = torch.float32) # b,w1,w2def orAdd(X,w): zhat = torch.mv(X,w).
2021-02-03 09:12:34
200
原创 与非门
import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)nandgate = torch.tensor([[1],[1],[1],[0]],dtype = torch.float32)w = torch.tensor([0.7,-0.5,-0.5] ,dtype = torch.float32) # b,w1,w2def nanAdd(X,w): zhat = torch.
2021-02-03 09:07:51
244
原创 与门画图
import torchimport matplotlib.pyplot as pltimport seaborn as snsX = torch.tensor([[1,0,0],[1,1,0],[1,0,1],[1,1,1]],dtype = torch.float32)sigma = torch.tensor([0.4502, 0.4875, 0.4875, 0.5250])andgate = torch.tensor([int(x) for x in sigma>=0.5], dt.
2021-02-03 08:38:48
309
原创 逻辑回归
#逻辑回归import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1],[1,1,1]],dtype = torch.float32)w = torch.tensor([-0.2,0.15,0.15],dtype = torch.float32)def LogisticR(X,w): zhat = torch.mv(X,w) #首先是线性回归 sigma = torch.sigmoid(zhat)#逻辑回归 andhat =
2021-02-03 07:59:15
134
原创 总结
import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)w = torch.tensor([-0.2,0.15,0.15] ,dtype = torch.float32) # b,w1,w2z = torch.tensor([-0.2, -0.05, -0.05, 0.1] ,dtype = torch.float32)def LineaR(X,w): zhat = tor
2021-02-02 17:49:41
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原创 softmax_dim=?_要注意
import torchfrom torch.nn import functional as FX = torch.tensor([[0,0],[1,0],[0,1],[1,1]], dtype = torch.float32)torch.random.manual_seed(420)dense = torch.nn.Linear(2,3)zhat = dense(X)print(zhat)sigma = F.softmax(zhat,dim=1)print(sigma)#sigma =.
2021-02-02 17:42:38
136
原创 F.torch.sigmoid
二分类import torchfrom torch.nn import functional as FX = torch.tensor([[0,0],[1,0],[0,1],[1,1]] ,dtype = torch.float32)torch.random.manual_seed(420)dense = torch.nn.Linear(2,1)zhat = dense(X)sigma = F.torch.sigmoid(zhat)y = [int(x) for x in sigm
2021-02-02 16:34:27
1611
原创 torch.nn.Linear
import torchX1 = torch.tensor([[0,0],[1,0],[0,1,],[1,1]] ,dtype = torch.float32)torch.random.manual_seed(420)output = torch.nn.Linear(2,1)zhat = output(X1)print(zhat)print(output.weight)print("*"*50)print(output.bias)
2021-02-02 11:58:47
137
原创 Pytorch 阶跃函数，与门电路
#阶跃函数，与门电路import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)andgate = torch.tensor([[0],[0],[0],[1]],dtype = torch.float32)w = torch.tensor([-0.2,0.15,0.15] ,dtype = torch.float32) # b,w1,w2def LinearRwithsign(X,w
2021-02-02 11:57:41
970
原创 Pytorch sigmoid函数，与门电路
#sigmoid函数，与门电路import torchX = torch.tensor([[1,0,0],[1,1,0],[1,0,1,],[1,1,1]] ,dtype = torch.float32)andgate = torch.tensor([[0],[0],[0],[1]],dtype = torch.float32)w = torch.tensor([-0.2,0.15,0.15] ,dtype = torch.float32) # b,w1,w2def LogisticR(X,w)
2021-02-02 11:56:32
647
原创 2021-02-01
import torchX = torch.tensor([[1.,0,0],[1,1,0],[1,0,1],[1,1,1]],dtype = torch.float32)w = torch.tensor([-0.2,0.15,0.15] ,dtype = torch.float32) # b,w1,w2z = torch.tensor([-0.2, -0.05, -0.05, 0.1] ,dtype = torch.float32)def LineaR(X,w): zhat = torc
2021-02-01 22:19:42
102
原创 Pytorch学习笔记
梯度下降入门import torchdef gradDescent(X, y, eps = torch.tensor(0.01, requires_grad = True), numIt = 1000): m, n = X.shape weights = torch.zeros(n, 1, requires_grad = True) for k in range(numIt): grad = torch.mm(X.t(), (torch.mm(X, weights
2021-01-31 20:43:41
113
原创 Pytorch学习笔记
第一周学习笔记整理(2)Lesson 2.张量的索引、分片、合并以及维度调整import torchimport numpy as np
2021-01-30 12:21:37
244
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原创 Pytorch学习笔记
Pytorch学习笔记第一周学习笔记整理// 矩阵的乘法import torchimport numpy as npt1 = torch.arange(1,7).reshape(2,3)t2 = torch.arange(1,10).reshape(3,3)torch.mm(t1,t2)
2021-01-30 11:20:23
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原创 复杂网络matlab学习记录（1）2019年4月1日
复杂网络matlab学习记录（1）2019年4月1日prim算法clc;clear;a=zeros(7);%首先生成一个7*7的零矩阵a(1,2)=50;a(1,3)=60;a(2,4)=65;a(2,5)=40;a(3,4)=52;a(3,7)=45;a(4,5)=50;a(4,6)=30;a(4,7)=42;a(5,6)=70;%把里面的元素变成图上的权a=a+a'...
2019-04-01 21:42:06
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