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This document now exists on the official ASP.NET core docs page.
You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis. | |
## Core Principles | |
1. EXPLORATION OVER CONCLUSION | |
- Never rush to conclusions | |
- Keep exploring until a solution emerges naturally from the evidence | |
- If uncertain, continue reasoning indefinitely | |
- Question every assumption and inference |
/* | |
File: UIImage+ImageEffects.h | |
Abstract: This is a category of UIImage that adds methods to apply blur and tint effects to an image. This is the code you’ll want to look out to find out how to use vImage to efficiently calculate a blur. | |
Version: 1.0 | |
Disclaimer: IMPORTANT: This Apple software is supplied to you by Apple | |
Inc. ("Apple") in consideration of your agreement to the following | |
terms, and your use, installation, modification or redistribution of | |
this Apple software constitutes acceptance of these terms. If you do | |
not agree with these terms, please do not use, install, modify or |
I used to have a site bookmarked with a table of all these functions, but the link is dead. Here's a matrix of Option and Result conversion functions. These become second nature once you have used Rust for any significant length of time, but it's useful to have a table reference.
For each of the below:
T
is the value possibly contained in an input Ok
Result
or Some
Option
.U
is a new value created by transforming or replacing an input T
. Note that when
U
appears in methods like map
, U ?= T
, for example by calling## Find Available Target Editions | |
DISM.exe /Online /Get-TargetEditions | |
## Convert Server Standard 2019 Evaluation to Server Standard 2019 | |
DISM /online /Set-Edition:ServerStandard /ProductKey:N69G4-B89J2-4G8F4-WWYCC-J464C /AcceptEula | |
## How To Activate | |
slmgr /ipk XXXXX-XXXXX-XXXXX-XXXXX-XXXXX | |
slmgr /skms [server]:[port] | |
slmgr /ato |
In the Generative AI Age your ability to generate prompts is your ability to generate results.
Claude 3.5 Sonnet and o1 series models are recommended for meta prompting.
Replace {{user-input}}
with your own input to generate prompts.
Use mp_*.txt
as example user-input
s to see how to generate high quality prompts.
/* C# code that sets up the mip colors texture: | |
s_MipColorsTexture = new Texture2D (32, 32, TextureFormat.RGBA32, true); | |
s_MipColorsTexture.hideFlags = HideFlags.HideAndDontSave; | |
Color[] colors = new Color[6]; | |
colors[0] = new Color (0.0f, 0.0f, 1.0f, 0.8f); | |
colors[1] = new Color (0.0f, 0.5f, 1.0f, 0.4f); | |
colors[2] = new Color (1.0f, 1.0f, 1.0f, 0.0f); // optimal level | |
colors[3] = new Color (1.0f, 0.7f, 0.0f, 0.2f); | |
colors[4] = new Color (1.0f, 0.3f, 0.0f, 0.6f); | |
colors[5] = new Color (1.0f, 0.0f, 0.0f, 0.8f); |
""" | |
This code was originally obtained from: | |
https://github.com/meta-llama/codellama/blob/main/llama/model.py | |
adapted from https://github.com/naver-ai/rope-vit/blob/main/self-attn/rope_self_attn.py | |
""" | |
import torch | |
import torch.nn as nn | |
from functools import partial | |
import einops |