ravnoor

Verify and Repair Disk Permissions via Terminal (Mac OS X)

Verify Permissions

diskutil verifyPermissions /

Repair Permissions

diskutil repairPermissions /

ravnoor

# tested on silius with conda python(2.7) installed

TOOLSDIR=/host/silius/local_raid/ravnoor/00_toolbox

conda install libgcc

######################################################
# build and install gcc > 4.8 (c++ 11 support)
wget http://ca.mirror.babylon.network/gcc/releases/gcc-4.9.4/gcc-4.9.4.tar.gz
tar xzf gcc-4.9.4.tar.gz

ravnoor

ravnoor

# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn, theano

# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1' 
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's. 
# Similarly, for h * W_2 + b_2
import theano
from theano import tensor as T
import numpy as np
from sklearn import datasets

ravnoor

# Example code to demonstrate parallel for loop implementation using joblib
from joblib import Parallel, delayed
import multiprocessing

# Vars
my_list = range(10)
squares = []

# Function to parallelize
def find_square(i):

ravnoor

find . -maxdepth 1 -name '._*' -delete

ravnoor

The fastest remote directory rsync over ssh archival I can muster (40MB/s over 1gb NICs)

This creates an archive that does the following:

rsync (Everyone seems to like -z, but it is much slower for me)

• a: archive mode - rescursive, preserves owner, preserves permissions, preserves modification times, preserves group, copies symlinks as symlinks, preserves device files.
• H: preserves hard-links
• A: preserves ACLs

ravnoor

conda create -n tf-keras python=2.7
pip install numpy

wget https://github.com/bazelbuild/bazel/releases/download/0.5.2/bazel-0.5.2-installer-linux-x86_64.sh
# 0.5.4 incompatibility issues

chmod +x bazel-0.5.2-installer-linux-x86_64.sh
HOME=/00_toolbox ./bazel-0.5.2-installer-linux-x86_64.sh --prefix=/00_toolbox/bazel-build

git clone https://github.com/tensorflow/tensorflow

ravnoor

# https://github.com/andreimouraviev/Mets/blob/a8ce43b335584187f0728a4b3975c679ccf06cbc/UNET_2D_AUG17.py
# coding: utf-8

# In[1]:

import os
os.chdir(r'/home/amourav/Python')
import sklearn
from UTILS import *

ravnoor

# https://github.com/Rachnog/Deep-Trading/blob/master/volatility/volatility.py

epsilon = 1.0e-9
def qlike_loss(y_true, y_pred):
    y_pred = K.clip(y_pred, epsilon, 1.0 - epsilon)
    loss = K.log(y_pred) + y_true / y_pred
    return K.mean(loss, axis=-1)

def mse_log(y_true, y_pred):
    y_pred = K.clip(y_pred, epsilon, 1.0 - epsilon)