syhw

"""
A deep neural network with or w/o dropout in one file.

License: Do What The Fuck You Want to Public License http://www.wtfpl.net/
"""

import numpy, theano, sys, math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams

syhw

# -*- coding: utf-8 -*- 
import os, re, random, math
from collections import Counter

""" Naive Bayes with Gibbs sampling, so it can deal with unlabeled data """
# as from "Gibbs Sampling for the Uninitiated" Philip Resnik, Eric Hardisty

def Dirichlet(v):
    """ takes a vector of counts v and returns a Multinomial ~ Dirichlet(v) """
    y = []

syhw

# -*- coding: utf-8 -*-
import itertools, random

import numpy as np
from scipy import linalg
import pylab as pl
import matplotlib as mpl
import math

epsilon = 10e-8

syhw

"""
A deep neural network with or w/o dropout in one file.
"""

import numpy
import theano
import sys
import math
from theano import tensor as T
from theano import shared

syhw

import numpy as np
from scipy.stats import bernoulli

N_EXPS = 200  # number of experiences to conduct TODO test 10k or 20k EXPS
N_BAGS = 10  # number of bags
N_DRAWS = 100  # number of draws
SMOOTHER = 1.E-2  # shrinkage parameter
EPSILON_BANDIT = 0.1  # epsilon-greedy bandit epsilon
EPSILON_NUM = 1.E-9  # numerical epsilon

syhw

#!/bin/bash

# tmux requires unrecognized OSC sequences to be wrapped with DCS tmux;
# <sequence> ST, and for all ESCs in <sequence> to be replaced with ESC ESC. It
# only accepts ESC backslash for ST.
function print_osc() {
    if [[ -n $TERM ]] ; then
        printf "\033Ptmux;\033\033]"
    else
        printf "\033]"

syhw

"""
A deep neural network with or w/o dropout in one file.
"""

import numpy
import theano
import sys
import math
from theano import tensor as T
from theano import shared

syhw

 category |          model              |     FLOPS     |     HPOPS     | AVX / cores / cuda cores...
CPU       | i9-8950HK (MacBookPro)      |  278 GFLOPS   |  556 GOPS?  | AVX2, 6 cores
CPU       | E5-2698 v4                  |  704 GFLOPS   |  1.4 TOPS?  | AVX2, 20 cores
CPU       | Xeon Plat. 8160 (~GCP/AWS)  |  3.2 TFLOPS   |  6.4 TOPS?  | AVX512 x2, 24 cores (2.1*24*512/32*2*2)
CPU       | Threadripper 2990WX         |  1.5 TFLOPS   |  3 TOPS?    | AVX2, 32 cores (3*32*256/32*2)
GPU       | K80                         |  8.7 TFLOPS   |             | 2496 cuda cores x2 (=4992)
GPU       | 1080 Ti                     | 10.6 TFLOPS   |             | 3584:224:88	
GPU       | AMD RX Vega 64              | 11.5 TFLOPS   |  23 TOPS    | 4096:256:64
GPU       | M60                         |  9.6 TFLOPS   |             | 2048:128:64 x2 (i.e. x2 GPU dies)
GPU       | P100 (NVLink)               | 10.6 TFLOPS   |  21 TOPS    | 3584:224:88?

syhw

"""
A deep neural network with or w/o dropout in one file.
"""

import numpy
import theano
import sys
import math
from theano import tensor as T
from theano import shared

syhw

import numpy as np
import matplotlib.pyplot as plt
from sklearn.neural_network import BernoulliRBM
from sklearn import linear_model, metrics
from sklearn.pipeline import Pipeline

X = np.array([[0,1,0,1,0,1,0,1,
              1,0,1,0,1,0,1,0,
              0,1,0,1,0,1,0,1,
              1,0,1,0,1,0,1,0,