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Vanova / Rinkeby.md
Created February 18, 2018 03:40 — forked from vietlq/Rinkeby.md
How to get on Rinkeby Testnet in less than 10 minutes

How to get on Rinkeby Testnet in less than 10 minutes

Following instructions from the excellent https://www.rinkeby.io/

Synchronizing a Full Node

A full node lets you access all state. There is a light node (state-on-demand) and wallet-only (no state) instructions as well,

def _isotonic_regression(np.ndarray[DOUBLE, ndim=1] y,
np.ndarray[DOUBLE, ndim=1] weight,
np.ndarray[DOUBLE, ndim=1] solution):
cdef:
Py_ssize_t current, i
unsigned int len_active_set
DOUBLE v, w
len_active_set = y.shape[0]
@Vanova
Vanova / conv_deconv_vae.py
Created March 25, 2017 13:44 — forked from kastnerkyle/conv_deconv_vae.py
Convolutional Variational Autoencoder, modified from Alec Radford at (https://gist.github.com/Newmu/a56d5446416f5ad2bbac)
# Alec Radford, Indico, Kyle Kastner
# License: MIT
"""
Convolutional VAE in a single file.
Bringing in code from IndicoDataSolutions and Alec Radford (NewMu)
Additionally converted to use default conv2d interface instead of explicit cuDNN
"""
import theano
import theano.tensor as T
from theano.compat.python2x import OrderedDict
@Vanova
Vanova / urban-sound-cnn-salamon.py
Created February 15, 2017 08:30 — forked from jaron/urban-sound-cnn-salamon.py
A Keras/Tensorflow implementation of the 5-layer CNN described in Salamon and Bello's paper (https://arxiv.org/pdf/1608.04363.pdf). See http://aqibsaeed.github.io/2016-09-24-urban-sound-classification-part-2/ for a description on how to create the data this uses.
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D
from keras.optimizers import SGD
from keras.regularizers import l2, activity_l2
from keras.utils import np_utils
from sklearn import metrics
# to run this code, you'll need to load the following data:
@Vanova
Vanova / latency.txt
Created May 27, 2016 08:01 — forked from jboner/latency.txt
Latency Numbers Every Programmer Should Know
Latency Comparison Numbers
--------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD