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#!/bin/sh | |
# MODS | |
#export PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/root/bin | |
#unset SESSION_MANAGER | |
#[ -r $HOME/.Xresources ] && xrdb $HOME/.Xresources | |
#xsetroot -solid grey |
## Refer to http://caffe.berkeleyvision.org/installation.html | |
# Contributions simplifying and improving our build system are welcome! | |
# cuDNN acceleration switch (uncomment to build with cuDNN). | |
# USE_CUDNN := 1 | |
# CPU-only switch (uncomment to build without GPU support). | |
CPU_ONLY := 1 | |
# uncomment to disable IO dependencies and corresponding data layers |
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 |
import sys | |
sys.path.append('..') | |
import os | |
import json | |
from time import time | |
import numpy as np | |
from tqdm import tqdm | |
from matplotlib import pyplot as plt | |
from sklearn.externals import joblib |
import os | |
import numpy as np | |
from matplotlib import pyplot as plt | |
from time import time | |
from foxhound import activations | |
from foxhound import updates | |
from foxhound import inits | |
from foxhound.theano_utils import floatX, sharedX |
import theano | |
import theano.tensor as T | |
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams | |
from theano.tensor.signal.downsample import max_pool_2d | |
from theano.tensor.extra_ops import repeat | |
from theano.sandbox.cuda.dnn import dnn_conv | |
from time import time | |
import numpy as np | |
from matplotlib import pyplot as plt |
""" | |
The MIT License (MIT) | |
Copyright (c) 2015 Alec Radford | |
Permission is hereby granted, free of charge, to any person obtaining a copy | |
of this software and associated documentation files (the "Software"), to deal | |
in the Software without restriction, including without limitation the rights | |
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
copies of the Software, and to permit persons to whom the Software is |
def adam(loss, all_params, learning_rate=0.001, b1=0.9, b2=0.999, e=1e-8, | |
gamma=1-1e-8): | |
""" | |
ADAM update rules | |
Default values are taken from [Kingma2014] | |
References: | |
[Kingma2014] Kingma, Diederik, and Jimmy Ba. | |
"Adam: A Method for Stochastic Optimization." | |
arXiv preprint arXiv:1412.6980 (2014). |