Dump existing data:
python3 manage.py dumpdata > datadump.json
Change settings.py to Postgres backend.
Make sure you can connect on PostgreSQL. Then:
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
| import tensorflow as tf | |
| from tensorflow.python.platform import gfile | |
| import numpy as np | |
| from imagenet_classes import class_names | |
| from scipy.misc import imread, imresize | |
| dir_name = 'mobilenet_v1_1.0_224' | |
| with tf.Graph().as_default() as graph: | |
| with tf.Session() as sess: | 
| <script> | |
| // Based on code from https://stackoverflow.com/questions/59629947/how-do-i-load-an-external-js-library-in-svelte-sapper | |
| import { onMount, createEventDispatcher } from "svelte"; | |
| const dispatch = createEventDispatcher(); | |
| export let src; | |
| export let libraryDetectionObject; | |
| let script; | |
| onMount(() => { |