aconz2

/* Times New Roman-based stack */
$timesNewRoman = Cambria, "Hoefler Text", Utopia, "Liberation Serif", "Nimbus Roman No9 L Regular", Times, "Times New Roman", serif

/* Modern Georgia-based serif stack */
$modernGeorgia = Constantia, "Lucida Bright", Lucidabright, "Lucida Serif", Lucida, "DejaVu Serif", "Bitstream Vera Serif", "Liberation Serif", Georgia, serif

/* Traditional Garamond-based serif stack */
$garamond = "Palatino Linotype", Palatino, Palladio, "URW Palladio L", "Book Antiqua", Baskerville, "Bookman Old Style", "Bitstream Charter", "Nimbus Roman No9 L", Garamond, "Apple Garamond", "ITC Garamond Narrow", "New Century Schoolbook", "Century Schoolbook", "Century Schoolbook L", Georgia, serif

/* Helvetica/Arial-based sans serif stack */

aconz2

List of components to remember

DOM

component/query component/classes component/value

DOM Events

Simple

aconz2

/**
 * Expose `Emitter`.
 */

module.exports = Emitter;

/**
 * Initialize a new `Emitter`.
 *
 * @api public

aconz2

#!/usr/bin/env python3

import pip

searcher = pip.commands.SearchCommand()
options, _ = searcher.parse_args([])
hits = searcher.search('*', options)
hits_transformed = pip.commands.search.transform_hits(hits)
for hit in hits_transformed:
  print(hit['name'])

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import numpy as np
from matplotlib import pyplot as plt
plt.ion()

# say you have a bunch of distributions you'd like to look at
data_sets = [np.random.poisson(lam, size=100), for lam in np.random.randint(1, 100, size=10)]

# in a REPL, this one-liner makes it easy to plot each one successively waiting for ENTER from the terminal
_ = [[plt.hist(data), input()] for data in data_sets]

aconz2

from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# original data
# not linearly separable in 2D
x = np.array([[1, 1], [-1, -1], [-1, 1], [1, -1]])

aconz2

#!/usr/bin/env python3

from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

normed = lambda v: v / np.linalg.norm(v)
# orthogonal vector in 2 space
orthogonal = lambda v: np.cross(v, [0, 0, 1])[:2]
pltvec = lambda v, **kwargs: plt.plot([0, v[0]], [0, v[1]], **kwargs)

aconz2

type exp =
  | Int of int
  | Succ of exp

(* This is what we want to write: *)
(* let rec step (e : exp) : exp option = *)
(*   match e with *)
(*   | Int _ -> None *)
(*   | Succ (Int i) -> Some (Int (i + 1)) *)
(*   | Succ e -> Some (Succ (step e)) *)

aconz2

type exp =
  | Int of int
  | Succ of exp
  | Plus of exp * exp

(* realistically we would want to specify depth and/or the bias of
choosing a certain expression *)
let rec gen_exp () : exp =
  match Random.int 3 with
  | 0 -> Int (Random.int 42)

aconz2

using CUDA on GPU 0...	
Make sure that your saved checkpoint was also trained with GPU. If it was trained with CPU use -gpuid -1 for sampling as well	
creating an lstm...	
missing seed text, using uniform probability over first character	
--------------------------	
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