levskaya

/* from: http://cautionsingularityahead.blogspot.com/2010/04/javascript-and-ieee754-redux.html */

function toIEEE754(v, ebits, fbits) {
 
        var bias = (1 << (ebits - 1)) - 1;
 
        // Compute sign, exponent, fraction
        var s, e, f;
        if (isNaN(v)) {
            e = (1 << bias) - 1; f = 1; s = 0;

levskaya

/**
  http://closure-library.googlecode.com/svn-history/r440/trunk/third_party/closure/goog/jpeg_encoder/jpeg_encoder_basic.js

 * @license
  Copyright (c) 2008, Adobe Systems Incorporated
  All rights reserved.

  Redistribution and use in source and binary forms, with or without
  modification, are permitted provided that the following conditions are
  met:

levskaya

-- For anyone who liked the PRIME DETECTOR puzzle included in some of the early access
-- builds of TIS-100...

-- INSTALLATION: Copy everything in this file. Open TIS-100. Go to the SPECIFICATION
-- EDITOR. Click on IMPORT SPECIFICATION FROM CLIPBOARD. Done!

-- The function get_name() should return a single string that is the name of the puzzle.
--
function get_name()
	return "PRIME DETECTOR"

levskaya

def top_k_top_p_filtering(logits, top_k=0, top_p=0.0, filter_value=-float('Inf')):
    """ Filter a distribution of logits using top-k and/or nucleus (top-p) filtering
        Args:
            logits: logits distribution shape (..., vocabulary size)
            top_k >0: keep only top k tokens with highest probability (top-k filtering).
            top_p >0.0: keep the top tokens with cumulative probability >= top_p (nucleus filtering).
    """
    top_k = min(top_k, logits.size(-1))  # Safety check
    if top_k > 0:
        # Remove all tokens with a probability less than the last token of the top-k

levskaya

In [2]: import tensorflow_datasets as tfds                                                                                                                                                                                                                                            
---------------------------------------------------------------------------                                                                                                                                                                                                           
AttributeError                            Traceback (most recent call last)                                                                                                                                                                                                           
<ipython-input-2-46a8a2031c9c> in <module>        
----> 1 import tensorflow_datasets as tfds                                                                                              

levskaya

import gc
import re
import jax
from jax import numpy as jnp
import numpy as np
from IPython import display
import pandas as pd


def natural_keys(text):

levskaya

Approachable PL Papers for Undergrads

On September 28, 2021, I asked on Twitter:

PL Twitter:

you get to recommend one published PL paper for an undergrad to read with oversight by someone experienced. the paper should be interesting, approachable, and (mostly) self-contained.

what paper do you recommend?

levskaya

from __future__ import annotations
from contextlib import contextmanager
from typing import NamedTuple, Callable, Optional, Any
import numpy as np

Array = Any

class Node(NamedTuple):
  vjp: Optional[Callable]
  parents: List[Node]