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mulderu / Lynx-start.md
Last active March 8, 2025 21:02
TikTok Lynx
@mulderu
mulderu / elixir-snipet.md
Created February 13, 2025 22:07
elixir snipet

learn

iex> states = %{"AL" => "Alabama",
%{"AL" => "Alabama", "WI" => "Wisconsin"}
"WI" => "Wisconsin" }
iex> responses = %{ { :error, :enoent } => :fatal, { :error, :busy } => :retry }
%{{:error, :busy} => :retry, {:error, :enoent} => :fatal}
iex> colors = %{ :red => 0xff0000, :green => 0x00ff00, :blue => 0x0000ff }
%{blue: 255, green: 65280, red: 16711680}
@mulderu
mulderu / lodash-chanin-example-jsbin.sasanut.js
Last active December 11, 2019 20:31
JS Bin// source https://jsbin.com/sasanut/4
// ref : https://medium.com/@parshwamehta13/basics-of-method-chaining-in-javascript-using-lodash-16f1168cf066
// <script src="https://cdn.jsdelivr.net/npm/[email protected]/lodash.min.js"></script>
var users = [
{
"user": "barney",
"age": 36
},
{
"user": "fred",
@mulderu
mulderu / dugan-trial.md
Created October 22, 2019 05:17
dugan config

DCGAN

128

Namespace(batchSize=1, beta1=0.5, cuda=True, dataroot='data', dataset='folder', imageSize=128, lr=0.0002, manualSeed=None, ndf=128, netD='', netG='', ngf=128, ngpu=1, niter=25, nz=2048, outf='output', workers=2) Generator(
  (main): Sequential(
    (0): ConvTranspose2d(2048, 1024, kernel_size=(4, 4), stride=(1, 1), bias=False)
    (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU(inplace)
@mulderu
mulderu / basic.array-js.md
Created September 10, 2019 05:43
javascript array basic 01

array operation : pop, push, shift, unshift, slice, splice

> a=[1,2,3,4,5,6,7]
[ 1, 2, 3, 4, 5, 6, 7 ]
> a.pop()
7
> a
[ 1, 2, 3, 4, 5, 6 ]
> a.shift()
1
@mulderu
mulderu / threejs-image-cube-list.html
Created July 15, 2019 02:55
example for three js texture in box
<!DOCTYPE html>
<html>
<head>
<title>learningthree.js boiler plate for three.js</title>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, user-scalable=no, minimum-scale=1.0, maximum-scale=1.0"
/>
@mulderu
mulderu / pytorch.mnist.py
Created June 26, 2019 19:13
pytorch mnist
from __future__ import print_function
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
class Net(nn.Module):
@mulderu
mulderu / index.html
Created January 23, 2019 07:37
JS Bin // source https://jsbin.com/nificif
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width">
<title>JS Bin</title>
<link href="https://code.jquery.com/ui/1.12.1/themes/smoothness/jquery-ui.css" rel="stylesheet" type="text/css" />
<script src="https://code.jquery.com/jquery-3.1.0.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/raphael/2.1.0/raphael-min.js"></script>
@mulderu
mulderu / index.html
Created January 23, 2019 04:44
JS Bin // source https://jsbin.com/nificif
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width">
<title>JS Bin</title>
<link href="https://code.jquery.com/ui/1.12.1/themes/smoothness/jquery-ui.css" rel="stylesheet" type="text/css" />
<script src="https://code.jquery.com/jquery-3.1.0.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/raphael/2.1.0/raphael-min.js"></script>
@mulderu
mulderu / html5-form-validation-01.html
Created January 12, 2019 13:08
html5 form validation and user message
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width">
<title>HTML5 Form Validation Ex</title>
<script src="https://code.jquery.com/jquery-3.1.0.js"></script>
</head>
<body>