Zhanwen Chen zhanwenchen

I wrote these instructions as part of "installing PyTorch with CUDA 12.1.1".

Anyway, if you still need to compile from source… here's how:

Build Magma from source

This is a dependency of PyTorch, which is sensitive to CUDA version.

Clone Magma:

	import torchvision

	class UnNormalize(torchvision.transforms.Normalize):
	def __init__(self,mean,std,args,*kwargs):
	new_mean = [-m/s for m,s in zip(mean,std)]
	new_std = [1/s for s in std]
	super().__init__(new_mean, new_std, args, *kwargs)

	# imagenet_norm = dict(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225])
	# UnNormalize(**imagenet_norm)

	"""
	Extract the contents of a `run-{id}.wandb` database file.

	These database files are stored in a custom binary format. Namely, the database
	is a sequence of wandb 'records' (each representing a logging event of some
	type, including compute stats, program outputs, experimental metrics, wandb
	telemetry, and various other things). Within these records, some data values
	are encoded with json. Each record is encoded with protobuf and stored over one
	or more blocks in a LevelDB log. The result is the binary .wandb database file.

	#!/bin/bash

	# Downloads and applies a patch from Drupal.org.
	if [ -z "$1" ]
	then
	echo "You need to supply a URL to a patch file."
	exit
	fi

	URL=$1;

	; /usr/share/pulseaudio/alsa-mixer/profile-sets/astro-a50-gen4.conf

	[General]
	auto-profiles = yes

	[Mapping analog-voice]
	description = Voice
	device-strings = hw:%f,0,0
	channel-map = left,right
	paths-output = steelseries-arctis-output-chat-common

	# Modify apt sources lists
	cd /etc/apt/sources.list.d/
	sudo rm gds-11-7.conf cuda-12-3.conf cuda-12-2.conf cuda-12-1.conf 989_cuda-11.conf cuda-ubuntu2004-11-7-local.list cuda-ubuntu2004-11-7-local.list

	# Modify apt preferences
	cd /etc/apt/preferences.d
	sudo rm cuda-repository-pin-600 nvidia-fabricmanager

	# Startup shell environment variables
	sudo vim /etc/profile.d/dlami.sh # comment out both

	git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git
	cd nv-codec-headers
	vi Makefile # change the first line to PREFIX = ${CONDA_PREFIX}
	make install
	cd ..

	git clone https://git.ffmpeg.org/ffmpeg.git
	cd ffmpeg
	git checkout n4.2.2
	conda install nasm

	"""
	Creates an HDF5 file with a single dataset of shape (channels, n),
	filled with random numbers.

	Writing to the different channels (rows) is parallelized using MPI.

	Usage:
	mpirun -np 8 python demo.py

	Small shell script to run timings with different numbers of MPI processes:

	# https://github.com/HDFGroup/hdf5/blob/hdf5-1_13_1/release_docs/INSTALL_parallel
	# https://docs.olcf.ornl.gov/software/python/parallel_h5py.html
	# https://www.pism.io/docs/installation/parallel-io-libraries.html
	# using ~/local/build/hdf5 as the build directory.
	# Install HDF5 1.13.1 with parallel I/O in ~/local/hdf5,

	version=1.13.1
	prefix=$HOME/local/hdf5
	build_dir=~/local/build/hdf5
	hdf5_site=https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.13