roman01la

#!/usr/bin/env bash
set -euo pipefail

# patch-claude-code.sh — Rebalance Claude Code prompts to fix corner-cutting behavior
#
# What this does:
#   Patches the npm-installed @anthropic-ai/claude-code cli.js to rebalance
#   system prompt instructions that cause the model to cut corners, simplify
#   excessively, and defer complicated work.
#

Qirias

void depth_pyramid(MTL::CommandBuffer *commandBuffer) {
    uint32_t zero = 0;
    memcpy(_spdAtomicBuffer->contents(), &zero, sizeof(uint32_t));

    MTL::ComputeCommandEncoder* encoder = commandBuffer->computeCommandEncoder();
    encoder->setLabel(NS::String::string("Depth Pyramid SPD", NS::ASCIIStringEncoding));

    encoder->setComputePipelineState(_depthPyramidPSO);
    encoder->setTexture(depthTexture, 0);
    encoder->setTexture(_depthPyramidTexture, 1);

dicknetherlands

# This gist shows how to speed up graphene_django by short-cutting the field and type resolution of the returned JSON and
# using a bit of caching to avoid having to repeat our discovery/decision process across multiple fields of the same
# type. It relies on trusting the developer to always return the correct types and respect non-nullability.

# Assumes that:
#   1. You're not using async code
#   2. You're using graphql_sync_dataloader to solve the N+1 problem
#   3. You're not using any graphene middleware other than for authentication
#   4. Your resolvers will all respect the schema
#   5. See code comments for further limitations

fbarretto

This is a gist on how to get StreamDiffusion running on a Mac (mps)

1. Clone the repo

git clone https://github.com/cumulo-autumn/StreamDiffusion.git

2. Setup the environment

cd StreamDiffusion

cpursley

PostgreSQL is Enough

See the new site: https://postgresisenough.dev

---

• Simplify: move code into database functions
• Just Use Postgres for Everything
• Just use Postgres
• PostgreSQL is the worlds’ best database

RobertRiachi

import torch
import torch.nn.functional as F
import coremltools as ct

from torch import Tensor
from torch import nn
from typing import Dict
from typing import Optional
from ane_transformers.reference.layer_norm import LayerNormANE as LayerNormANEBase
from coremltools.models.neural_network.quantization_utils import quantize_weights

Martini024

import AVKit
import Foundation

class VideoHelper {

    static func getThumbnail(from player: AVPlayer, at time: CMTime, maximumSize: CGSize? = nil) -> CGImage? {
        guard let currentItem = player.currentItem else { return nil }
        return getThumbnail(from: currentItem.asset, at: time, maximumSize: maximumSize)
    }

moutend

[Swift] Equalizing Audio Signal with vDSP.Biquad

This script reads /tmp/input.wav, applies the low-pass filter, and writes the modified signal as /tmp/output.wav.

To run, open Terminal.app and hit the following command:

$ swift main.swift

madelinegannon

How to Set Up the NVIDIA Jetson Nano for openFrameworks

A Step-By-Step Guide from Unboxing to Creative Coding

Getting Started

1. Set up and Configure the Nano
2. Set up and Configure openFrameworks
   • Getting the Nightly Build
   • Editing MAKE files
   • Recompile with New Configs

• Finish openFrameworks Linux Setup

kylemcdonald

# based on https://github.com/kylerbrown/ezdtw
# with modifications to be fully njit-able

import numpy as np
from numba import njit

@njit
def sqeuclidean(a, b):
    return np.sum((a - b)**2)