namakemono

from keras.layers import *
from keras.activations import softmax
from keras.models import Model

"""

References
----------
[1]. Parikh, Ankur P., et al. "A decomposable attention model for natural language inference." arXiv preprint arXiv:1606.01933 (2016).

inchoate

The Problem

The documentation for how to deploy a pipeline with extra, non-PyPi, pure Python packages on GCP is missing some detail. This gist shows how to package and deploy an external pure-Python, non-PyPi dependency to a managed dataflow pipeline on GCP.

TL;DR: You external package needs to be a python (source/binary) distro properly packaged and shipped alongside your pipeline. It is not enough to only specify a tar file with a setup.py.

Preparing the External Package

Your external package must have a proper setup.py. What follow is an example setup.py for our ETL package. This is used to package version 1.1.1 of the etl library. The library requires 3 native PyPi packages to run. These are specified in the install_requires field. This package also ships with custom external JSON data, declared in the package_data section. Last, the setuptools.find_packages function searches for all available packages and returns that

bistaumanga

'''Implementation and of K Means Clustering
Requires : python 2.7.x, Numpy 1.7.1+'''
import numpy as np

def kMeans(X, K, maxIters = 10, plot_progress = None):

    centroids = X[np.random.choice(np.arange(len(X)), K), :]
    for i in range(maxIters):
        # Cluster Assignment step
        C = np.array([np.argmin([np.dot(x_i-y_k, x_i-y_k) for y_k in centroids]) for x_i in X])

velicast

// C++ includes used for precompiling -*- C++ -*-

// Copyright (C) 2003-2013 Free Software Foundation, Inc.
//
// This file is part of the GNU ISO C++ Library.  This library is free
// software; you can redistribute it and/or modify it under the
// terms of the GNU General Public License as published by the
// Free Software Foundation; either version 3, or (at your option)
// any later version.

yanofsky

This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit

jboner

Latency Comparison Numbers (~2012)
----------------------------------
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