RuQing Xu xrq-phys

## INSTALL.md

      
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                — forked from takeit/INSTALL.md
            
              
                macFUSE + NTFS-3G still supported on macOS 14.5 + M-series chip!
              
          
    This guide is intended to provide a OSS-based solution for enabling NTFS read+write access on modern macOS.
In the meantime, I see some commercial and semi-commercial solutions for NTFS on mac. Some of them are excellent, others might have a debatable reputation. Discretion is stronly adviced there.
本说明旨在介绍一个在现代macOS平台（包括M1/M2等新架构和Intel老架构mac电脑）上可用的NTFS读写模式的挂载方案。
该方案拷贝自 takeit/INSTALL.md，当时在macOS Sierra上可用使用但作者述说需要关闭SIP。本文经测试该方案实有不影响SIP的用法。
NTFS for macOS的商业或半商业的解决方案较为鱼龙混杂，亦存在部分组织误导用户认为「只有少数解决方案能支持最新系统架构」。实际上，macFUSE至今仍被维护，ntfs-3g也仍然可用（编译很快）。希望大家仔细甄别。
1. Install macFUSE:


## softplus.hh
/**
 * This Source Code Form is subject to the terms of the Mozilla Public
 * License, v. 2.0. If a copy of the MPL was not distributed with this
 * file, You can obtain one at https://mozilla.org/MPL/2.0/.
 */
#pragma once
#include <complex>
#include <algorithm>

// Real softplus.

## MLComputeGEMM.swift
import Foundation
import MLCompute
import PlaygroundSupport

let iPage = PlaygroundPage.current
iPage.needsIndefiniteExecution = true

/*
 * Apple says MLCMatMulLayer does a ``batch matrix multiplication''
 *   but didn't make clear its meaning.

## A-Guide-to-Build-NumPy-on-Apple-Silicon.md

      
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                xrq-phys
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              December 11, 2020 22:17
            
              
                Compile NumPy on M1 Chip, with Code Attached.
              
          
    What
Compile NumPy on Apple Silicon M1 Chip
How

Create virtual env at, say export VENV=$HOME/.local:

python3 -m venv $VENV
. $VENV/bin/activate

  
## batch_define.jl
module BatchDef

macro def_numed_fun(funname, num)
    numed_funname = Symbol(string(funname, num))
    @show numed_funname
    return quote
        $(esc(numed_funname))() = $num
    end
end

## contract_fwd_prototype.jl
# here idx has 3 entries corresponding to e.g. "ik,jk->ij".
contract!(A::Array{T},
          B::Array{T},
          C::Array{T},
          idx) where {T<:Dual} = contract!(T, sizeof(T)/sizeof(tovalue(T)), # tovalue unveils base type.
                                           A, 0, B, 0, C, 0, idx)

contract!(Type::Dual{Tg, T, ND}, topst, # top-level stride
          A::Array, sftA, # arrays here are all at their top-level (not dispatched)
          B::Array, sftB,

## Code_OSS_Aarcha64.md

      
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              December 26, 2020 07:57
            
              
                [DEPRECATED: Official Available] Installing Native Aarch64 VSCode on Windows on Arm Devices
              
          
    This guide is a summation of current situation as of Apr. 26, 2020,
on how to build and use native Aarch64 (ARM64) Visual Studio Code on
devices like Surface Pro X.
References


This Issue on Official Repo;
The MS Contribution Guidle;
This Pull Request;
And This Build Sample.


## example_bli_ker_call.cc
#include <iostream>
#include <blis/blis.h>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/io.hpp>

int main(const int argc, const char *argv[])
{
    // these two doesn't conflict.
    using namespace std;
    using namespace boost::numeric::ublas;

## Tensordot.jl
"""
    Tensordot.jl - Minimal Tensordot Implementation

Minimal tensordot for supporting Zygote's automatic differentiation.
This bunch of code is also compatible with FluxML's Tracker module.
"""
module Tensordot

using Zygote: @adjoint
using LinearAlgebra

## compile_MathLink_linux.sh
#!/bin/bash

# 1. Installation location of the Wolfram Engine
WOLFRAMROOT=/usr/local/Wolfram/WolframEngine/12.1
# 2. MathLink path. Consider saving it for reasons in 4.
MLINKROOT=$WOLFRAMROOT/SystemFiles/Links/MathLink/DeveloperKit/Linux-x86-64/CompilerAdditions

# 3. Compile
gcc -m64 -o ~/.TeXmacs/bin/tm_mathematica.bin \
  /usr/share/TeXmacs/plugins/mathematica/src.lazy/tm_mathematica.c \
	/**
	* This Source Code Form is subject to the terms of the Mozilla Public
	* License, v. 2.0. If a copy of the MPL was not distributed with this
	* file, You can obtain one at https://mozilla.org/MPL/2.0/.
	*/
	#pragma once
	#include <complex>
	#include <algorithm>

	// Real softplus.
	import Foundation
	import MLCompute
	import PlaygroundSupport

	let iPage = PlaygroundPage.current
	iPage.needsIndefiniteExecution = true

	/*
	* Apple says MLCMatMulLayer does a ``batch matrix multiplication''
	* but didn't make clear its meaning.
	module BatchDef

	macro def_numed_fun(funname, num)
	numed_funname = Symbol(string(funname, num))
	@show numed_funname
	return quote
	$(esc(numed_funname))() = $num
	end
	end
	# here idx has 3 entries corresponding to e.g. "ik,jk->ij".
	contract!(A::Array{T},
	B::Array{T},
	C::Array{T},
	idx) where {T<:Dual} = contract!(T, sizeof(T)/sizeof(tovalue(T)), # tovalue unveils base type.
	A, 0, B, 0, C, 0, idx)

	contract!(Type::Dual{Tg, T, ND}, topst, # top-level stride
	A::Array, sftA, # arrays here are all at their top-level (not dispatched)
	B::Array, sftB,
	#include <iostream>
	#include <blis/blis.h>
	#include <boost/numeric/ublas/matrix.hpp>
	#include <boost/numeric/ublas/io.hpp>

	int main(const int argc, const char *argv[])
	{
	// these two doesn't conflict.
	using namespace std;
	using namespace boost::numeric::ublas;
	"""
	Tensordot.jl - Minimal Tensordot Implementation

	Minimal tensordot for supporting Zygote's automatic differentiation.
	This bunch of code is also compatible with FluxML's Tracker module.
	"""
	module Tensordot

	using Zygote: @adjoint
	using LinearAlgebra
	#!/bin/bash

	# 1. Installation location of the Wolfram Engine
	WOLFRAMROOT=/usr/local/Wolfram/WolframEngine/12.1
	# 2. MathLink path. Consider saving it for reasons in 4.
	MLINKROOT=$WOLFRAMROOT/SystemFiles/Links/MathLink/DeveloperKit/Linux-x86-64/CompilerAdditions

	# 3. Compile
	gcc -m64 -o ~/.TeXmacs/bin/tm_mathematica.bin \
	/usr/share/TeXmacs/plugins/mathematica/src.lazy/tm_mathematica.c \