hollance

#pragma once

#include <cmath>

/**
  State variable filter (SVF), designed by Andrew Simper of Cytomic.

  http://cytomic.com/files/dsp/SvfLinearTrapOptimised2.pdf

  The frequency response of this filter is the same as of BZT filters.

hollance

    0 poke808,225:gosub 31000
    1 poke53269,0
   10 remifa=0thena=1:load"c.font3",8,1
   20 remifa=1thena=2:load"lespirites",8,1
  900 ww=68:dim n(ww):dim keer$(50)
 1000 rem *** the game ***
 1010 rem ** after a game over **
 1015 poke 53265,peek(53265) and 239
 1020 sc=0:gd=0:ft=0:ln=0:l$="":w$="":keer=1:keer$(0)="":keer$(1)=""
 1030 gosub 20000:gosub 10000:jaja=0

hollance

# Convert SE-ResNet-50 from Caffe to Keras
# Using the model from https://github.com/shicai/SENet-Caffe

import os
import numpy as np

# The caffe module needs to be on the Python path; we'll add it here explicitly.
import sys
caffe_root = "/path/to/caffe"
sys.path.insert(0, caffe_root + "python")

hollance

To allow the Hugging Face version of Whisper to predict word-level timestamps, a new property alignment_heads must be added to the GenerationConfig object. This is a list of [layer, head] pairs that select the cross-attention heads that are highly correlated to word-level timing.

If your Whisper checkpoint does not have the alignment_heads property yet, it can be added in two possible ways.

Method 1. Change the model.generation_config property:

# load the model
model = WhisperForConditionalGeneration.from_pretrained("your_checkpoint")

hollance

@interface NSObject (MHOverride)

/*
 * Dynamically overrides the specified method on this particular instance.
 *
 * The block's parameters and return type must match those of the method you
 * are overriding. However, the first parameter is always "id _self", which
 * points to the object itself.
 *

hollance

import CoreML
import Combine

extension Publisher where Self.Output: MLFeatureProvider {
  /**
   Operator that lets you run a Core ML model as part of a Combine chain.

   It accepts an MLFeatureProvider object as input, and, if all goes well,
   returns another MLFeatureProvider with the model outputs.

hollance

; *****************************************************************************
;
; $VER: ZeroGravity Source 1.0 (C) 1997 Matthijs Hollemans
;
; *****************************************************************************
;
; This is the full source code to Zero Gravity. I used the very cool ASM-One
; V1.29 assembler from T.F.A. but that doesn't matter anyway because you won't
; be able to reassemble this without the required binary includes...
;

hollance

/*
  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.
 

hollance

Barfdown: a Markdown-ish Parser Written in Swift

Goals for this project:

• Parse a simplified version of Markdown that is good enough for writing my blog posts.
• Be reasonably efficient. This means the parser shouldn't copy substrings around if not necessary. This is done by storing all the elements as indexes into the original text.
• Be small and therefore be easy to understand.
• No regular expressions. They are the lazy person's solution to parsing. ;-)

This is just a toy project for me to experiment with writing parsers in Swift. Because why not?

hollance

/*
  Joseph Weizenbaum's classic ELIZA chat bot in Swift.

  Based on the IBM PC BASIC program from CREATIVE COMPUTING by Patricia
  Danielson and Paul Hashfield, and the Java adaptation by Jesper Juul.
  
  Run this script from Terminal:
  $ swift eliza.swift
  
  Press Ctrl-C or Ctrl-D to quit. (Or type "shut up".)