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@MihailCosmin
MihailCosmin / cuda_11.8_installation_on_Ubuntu_22.04
Last active June 30, 2024 16:27 — forked from primus852/cuda_11.7_installation_on_Ubuntu_22.04
Instructions for CUDA v11.8 and cuDNN 8.7 installation on Ubuntu 22.04 for PyTorch 2.0.0
#!/bin/bash
### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###
### to verify your gpu is cuda enable check
@robhrt7
robhrt7 / MySQL_5-7_macOS.md
Last active February 28, 2024 03:48 — forked from nrollr/MySQL_macOS_Sierra.md
Install MySQL 5.7 on macOS using Homebrew

This is a fork of original gist https://gist.github.com/nrollr/3f57fc15ded7dddddcc4e82fe137b58e, with slight changes on pointing to 5.7 version branch, instead of 8 (latest default of MySQL in Hombrew).

Install MySQL 5.7 on macOS

This procedure explains how to install MySQL using Homebrew on macOS (Sierra 10.12 and up)

Install Homebrew

  • Installing Homebrew is effortless, open Terminal and enter :
    $ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
  • Note: Homebrew will download and install Command Line Tools for Xcode 8.0 as part of the installation process.
@jdesive
jdesive / setup.md
Created January 28, 2018 00:00
Mount NFS share from synology NAS to Ubuntu

Mount Synology NFS share to Ubuntu 16.04

I have all hardware virtualized in ESXi 6.5...
Synology DSM 5.2-5644
Ubuntu 16.04

Start

On your fresh install on Ubuntu 16.04:

  1. Click the Connections icon on the top bar
  2. Goto Edit Connections
@swyoon
swyoon / np_to_tfrecords.py
Last active November 29, 2022 06:39
From numpy ndarray to tfrecords
import numpy as np
import tensorflow as tf
__author__ = "Sangwoong Yoon"
def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
"""
Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
For supervised learning, feed training inputs to X and training labels to Y.
For unsupervised learning, only feed training inputs to X, and feed None to Y.
@WIStudent
WIStudent / Instructions.md
Last active November 16, 2018 08:15
Compiling DeepMatching's GPU version on Ubuntu 16.10

Compiling DeepMatching's GPU version on Ubuntu 16.10

DeepMatching is an algorithm that finds corresponding points in two images. Its GPU implementation was written for Fedora 21, which makes things a bit more difficult if you want to run it on an Ubuntu system. This document contains step-by-step instructions on how to get DeepMatching running on Ubuntu 16.10. I only tested it with Ubuntu 16.10, just let me know if it works with previous versions too.

To compile the GPU version you first need to compile the Caffe version that is included that comes with the DeepMatching files. Newer versions of Caffe won't work because Caffe changed the structure of its header files.

Compiling Caffe

Before compiling Caffe we need to make sure all its dependencies are installed. From the installation guide for Ubuntu 16.04/15.10:

sudo apt-get install build-essential cmake git pkg-config
@kylemcdonald
kylemcdonald / CameraImage.cpp
Created November 23, 2015 15:30
openFrameworks app for sending images to disk for processing, and reading text back from disk. Used for "NeuralTalk and Walk".
#include "ofMain.h"
#include "ofxTiming.h"
class ofApp : public ofBaseApp {
public:
ofVideoGrabber grabber;
DelayTimer delay;
ofTrueTypeFont font;
string description;
@karpathy
karpathy / min-char-rnn.py
Last active June 28, 2024 06:13
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)