tartavull

import inspect
import ast
from textwrap import dedent

import tensorflow as tf

def escape_op_name(name):
  """
  It has to match with "^[A-Za-z0-9.][A-Za-z0-9_.\\-/]*$"
  """

ayman

alias happendToFile='hdfs dfs -appendToFile'
alias hcat='hdfs dfs -cat'
alias hchecksum='hdfs dfs -checksum'
alias hchgrp='hdfs dfs -chgrp'
alias hchmod='hdfs dfs -chmod'
alias hchown='hdfs dfs -chown'
alias hcopyFromLocal='hdfs dfs -copyFromLocal'
alias hcopyToLocal='hdfs dfs -copyToLocal'
alias hcount='hdfs dfs -count'
alias hcp='hdfs dfs -cp'

joyrexus

collapsible markdown?

CLICK ME

yes, even hidden code blocks!

print("hello world!")

rtbs-dev

4rzael

NOTE : Take a look at the comments below !

GIS with pySpark : A not-so-easy journey

Why would you do that ?

Today, many datas are geolocalised (meaning that they have a position in space). They're named GIS datas.

It's not rare that we need to do operations on those, such as aggregations, and there are many optimisations existing to do that.

danijar

# Example for my blog post at:
# http://danijar.com/introduction-to-recurrent-networks-in-tensorflow/
import functools
import sets
import tensorflow as tf


def lazy_property(function):
    attribute = '_' + function.__name__

danijar

# Example for my blog post at:
# https://danijar.com/introduction-to-recurrent-networks-in-tensorflow/
import functools
import sets
import tensorflow as tf


def lazy_property(function):
    attribute = '_' + function.__name__

danijar

# Working example for my blog post at:
# https://danijar.github.io/structuring-your-tensorflow-models
import functools
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data


def doublewrap(function):
    """
    A decorator decorator, allowing to use the decorator to be used without

Cospel

#http://blog.echen.me/2011/07/18/introduction-to-restricted-boltzmann-machines/
#https://www.tensorflow.org/versions/r0.7/api_docs/python/constant_op.html#random_uniform

import tensorflow as tf
import numpy as np
import input_data
import Image
from util import tile_raster_images

ottokart

# Tiny example of 3-layer nerual network with dropout in 2nd hidden layer
# Output layer is linear with L2 cost (regression model)
# Hidden layer activation is tanh

import numpy as np

n_epochs = 100
n_samples = 100
n_in = 10
n_hidden = 5