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import time
from numpy import *

def dottest(type, dim):
    t = time.time()
    a = random.random((dim, dim)).astype(type)
    b = random.random((dim, dim)).astype(type)
    c = dot(a, b)
    ct = time.time() - t
    print "++++++++++++++++++++++++"

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import nltk

text = """The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital
computer or the gears of a cycle transmission as he does at the top of a mountain
or in the petals of a flower. To think otherwise is to demean the Buddha...which is
to demean oneself."""

# Used when tokenizing words
sentence_re = r'''(?x)      # set flag to allow verbose regexps
      ([A-Z])(\.[A-Z])+\.?  # abbreviations, e.g. U.S.A.

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'''This scripts implements Kim's paper "Convolutional Neural Networks for Sentence Classification"
with a very small embedding size (20) than the commonly used values (100 - 300) as it gives better
result with much less parameters.

Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_cnn.py

Get to 0.853 test accuracy after 5 epochs. 13s/epoch on Nvidia GTX980 GPU.
'''

from __future__ import print_function

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On Mac OS (host):

Shutdown your VM and do:

VirtualBox > Settings > Network > Add (you will get vboxnet0)

On a terminal ifconfig will show you new interface vboxnet0

VM's Settings > System > check "Enable I/O APIC." VM's Settings > Network > Adapter 2 > host-only vboxnet0

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# Online backup a sqlite3 DB.
# python3 sqlite_online_backup.py db_to_backup.sqlite backup_db.sqlite

import sqlite3
import sqlitebck
import sys

fname_to_backup = sys.argv[1]
fname_backup = sys.argv[2]

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import numpy as np
import numpy.random as npr
import time

# --- Test 1
N = 100
n = 2000

A = npr.randn(n, n)
B = npr.randn(n, n)

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import torch
import time

# --- Test 1
N = 10
n = 1000

A = torch.randn(n, n)
B = torch.randn(n, n)

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