aka what i did to get from nothing to done.
note: these are designed to be primarily a re-install guide for myself (writing things down helps me memorize the knowledge), as such don't take any of this on blind faith - some areas are well tested and the docs are very robust, some items, less so). YMMV
| """ | |
| 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) |
This guide is how I got a Coral TPU (USB) working in an unprivileged LXC container.
At the end, you should be able to use the Coral TPU for inferencing inside of an unprivileged LXC container as well as Docker containers within the LXC, such as Frigate.
This does NOT require privileged LXC or docker container.
NOTES:
Since PWM is a little fraught with gotchas, this is mostly a message to future me-
(Note to self, rtfm - https://datasheets.raspberrypi.com/rp1/rp1-peripherals.pdf)
| pin | a0 | a3 |
|---|---|---|
| GPIO19 | PWM0_CHAN3 | |
| GPIO18 | PWM0_CHAN2 |
Based on https://github.com/frappe/frappe_docker/blob/main/docs/development.md
Clone git repo
git clone https://github.com/frappe/frappe_docker.git
cd frappe_docker
| /* | |
| clang++ -Wall -o testshunt testshunt.c /usr/lib/libgattlib.so | |
| */ | |
| #include <assert.h> | |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| #include <stdbool.h> | |
| #include "gattlib.h" |
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
| using UnityEngine; | |
| using System.Collections.Generic; | |
| [RequireComponent(typeof(MeshRenderer))] | |
| [RequireComponent(typeof(MeshFilter))] | |
| public class GridMesh : MonoBehaviour | |
| { | |
| public int GridSize; | |
| void Awake() |
| { | |
| "version": 1, | |
| "snippets": [ | |
| { | |
| "version": 1, | |
| "javascript": "const settings \u003d {\\r\\n chatGpt: {\\r\\n \\/\\/ replace with your ChatGPT API key created at https:\\/\\/platform.openai.com\\/api-keys\\r\\n apiKey: \\\u0027ENTER CHATGPT API KEY\\\u0027,\\r\\n\\r\\n \\/\\/ the OpenAI model to use\\r\\n model: \\\u0027gpt-4-turbo\\\u0027,\\r\\n },\\r\\n alsoAsked: {\\r\\n \\/\\/ replace with your AlsoAsked API key created at https:\\/\\/alsoasked.com\\/developer\\/keys\\r\\n apiKey:\\r\\n \\\u0027ENTER ALSOASKED API KEY\\\u0027,\\r\\n\\r\\n \\/\\/ the language to search in\\r\\n language: \\\u0027en\\\u0027,\\r\\n\\r\\n \\/\\/ the region to search in\\r\\n region: \\\u0027gb\\\u0027,\\r\\n\\r\\n \\/\\/ the depth of the search\\r\\n \\/\\/ 2 is the default and returns the smallest number of questions, and costs 1 credit\\r\\n \\/\\/ 3 is the maximum and returns the largest number of questions, but costs 4 credits\\r\\n depth: 2,\\r\\n\\r\\n |
| FROM alpine as builder | |
| RUN apk add --no-cache build-base nasm | |
| COPY . . | |
| RUN nasm -f elf64 -o server.o server.s && ld server.o -o server | |
| FROM alpine | |
| COPY --from=0 /server /server | |
| CMD /server $PORT |