| defmodule Training.Example do | |
| def train() do | |
| Nx.default_backend(EXLA.Backend) | |
| {:ok, spec} = | |
| Bumblebee.load_spec({:hf, "prajjwal1/bert-medium"}, | |
| module: Bumblebee.Text.Bert, | |
| architecture: :for_sequence_classification | |
| ) |
| ## For a beginner-friendly version of the following (more advanced users likely will get better use of the below, | |
| ## if you're just starting out...), see this new gist: | |
| ## https://gist.github.com/WolfgangSenff/0a9c1d800db42a9a9441b2d0288ed0fd | |
| This document represents the beginning of an upgrade or migration document for GDScript 2.0 and Godot 4.0. I'm focusing on 2D | |
| at the moment as I'm upgrading a 2D game, but will hopefully have more to add for 3D afterward. | |
| ## If you want more content like this, please help fund my cat's medical bills at https://ko-fi.com/kyleszklenski - thank you very much! On to the migration guide. |
Field types are marked using C-style notation:
char[4] indicates a 4-byte fixed-width stringuint[6] indicates a 6-byte sequenceuint8, uint16, and uint32 are unsigned byte, short, and long integersint8, int16, and int32 are signed byte, short, and long integers
| # First, we need to find our device. BEFORE inserting your USB drive, run the | |
| # following: | |
| diskutil list | |
| # This will output a bunch of info about all of the disk drives connected to | |
| # your Mac. Each entry will have a header in the form "/dev/diskX", where X is | |
| # some number starting at 0. Now, insert your USB drive and run the command | |
| # again. You should see a new entry. Make note of the name (ie, /dev/diskX). | |
| diskutil list |
| /* | |
| The "hello world" of neural networks: a simple 3-layer feed-forward | |
| network that implements an XOR logic gate. | |
| The first layer is the input layer. It has two neurons a and b, which | |
| are the two inputs to the XOR gate. | |
| The middle layer is the hidden layer. This has two neurons h1, h2 that | |
| will learn what it means to be an XOR gate. | |
| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
| // Copyright 2014 Olivier Gillet. | |
| // | |
| // Author: Olivier Gillet (ol.gillet@gmail.com) | |
| // | |
| // Permission is hereby granted, free of charge, to any person obtaining a copy | |
| // of this software and associated documentation files (the "Software"), to deal | |
| // in the Software without restriction, including without limitation the rights | |
| // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| // copies of the Software, and to permit persons to whom the Software is | |
| // furnished to do so, subject to the following conditions: |
| KEYBINDINGS | |
| byobu keybindings can be user defined in /usr/share/byobu/keybindings/ (or within .screenrc if byobu-export was used). The common key bindings | |
| are: | |
| F2 - Create a new window | |
| F3 - Move to previous window | |
| F4 - Move to next window |
