Eric GreenEric

## flux_vae.jl
# adapted from
# Keras_code_sample_for_Google_IO_2021
# Modern Keras design patterns | Session
# https://www.youtube.com/watch?v=FCz9m4T0DI0
# code: https://goo.gle/3t0rSpo
# by Martin Gorner, François Chollet

using Flux
using MLDatasets
using Random

## Learn-Julia-zh-cn.jl
# 单行注释由「#」号开始
#= 以「#=」开头，用「=#」结尾就可以得到多行注释
  多行注释可以嵌套。
=#

# VSC 代码高亮 patch'

####################################################
## 1. 原始类型与操作符
####################################################

## eigenvectors_from_eigenvaluies.R
# Generate random matrix with dim = N
N <- 3
A <- matrix(runif(N*N), N, N, byrow=TRUE)
A <- A+t(A)

# Setting up eigenvalues lambda, true eigenvector V and derived eigenvector U
ev <- eigen(A)
(lambda <- ev$values)
(V <- ev$vectors)
U <- matrix(0L, N, N)
	# adapted from
	# Keras_code_sample_for_Google_IO_2021
	# Modern Keras design patterns \| Session
	# https://www.youtube.com/watch?v=FCz9m4T0DI0
	# code: https://goo.gle/3t0rSpo
	# by Martin Gorner, François Chollet

	using Flux
	using MLDatasets
	using Random
	# 单行注释由「#」号开始
	#= 以「#=」开头，用「=#」结尾就可以得到多行注释
	多行注释可以嵌套。
	=#

	# VSC 代码高亮 patch'

	####################################################
	## 1. 原始类型与操作符
	####################################################
	# Generate random matrix with dim = N
	N <- 3
	A <- matrix(runif(N*N), N, N, byrow=TRUE)
	A <- A+t(A)

	# Setting up eigenvalues lambda, true eigenvector V and derived eigenvector U
	ev <- eigen(A)
	(lambda <- ev$values)
	(V <- ev$vectors)
	U <- matrix(0L, N, N)