Prepare sc for py transform (#35)

* enable notebook on bigdl_0.3.0 and spark_2.2

* changes according to code changes

* remove changes on start_notebook.sh

* 0.3.0 notebook work

* Fix docs

* unsaved changes

* change README address for 0.3.0 download

* change README

* prepare sc for jenkins

* fix matplotlib import

* declare utf-8 coding

* more declares

* spark conf to avoid OOM

* change to directly use jupyter

* specify version 0.3.0 , delete spark install in Setup.md for pyspark will be installed with pip

* setup changes

* setup changes

README.md

@@ -27,10 +27,8 @@ Step-by-step Deep Leaning Tutorials on Apache Spark using [BigDL](https://github
 + [Setup env on Mac OS](https://github.com/intel-analytics/BigDL-Tutorials/blob/master/SetupMac.md) / [Setup env on Linux](https://github.com/intel-analytics/BigDL-Tutorials/blob/master/SetupLinux.md)
 
 ### Start Jupyter Server
-* Download BigDL 0.3.0([linux or mac](https://repo1.maven.org/maven2/com/intel/analytics/bigdl/dist-spark-2.2.0-scala-2.11.8-linux64/0.3.0/dist-spark-2.2.0-scala-2.11.8-linux64-0.3.0-dist.zip )) and unzip file.
-* Run ```export BIGDL_HOME=where is your unzipped bigdl folder```
-* Run ```export SPARK_HOME=where is your unpacked spark folder```
-* Run ```./start_notebook.sh```
+* Run ```pip install BigDL==0.3.0```
+* Run ``` jupyter notebook --notebook-dir=./ --ip=* --no-browser```
 
 ## Run Demo
 * Open a browser - Suggest Chrome or Firefox or Safari

SetupLinux.md

@@ -6,9 +6,13 @@ This guide is mainly for Ubuntu. If you has other linux platform, please do the
 
 ###  Installation Steps
 
-* Install Java and Spark
+* Install Java 
    * Install Jdk 8 from http://www.oracle.com/technetwork/java/javase/downloads/index-jsp-138363.html#javasejdk
-   * Install Spark 2.1.0 from http://spark.apache.org/downloads.html
+   * Run the following steps
+```
+   export JAVA_HOME=where you unzip your jdk
+   export PATH=$PATH:$JAVA_HOME/bin
+```
 * Install Python dev env. Python2.7 is shipped with linux.
 ```
     sudo apt-get update

SetupMac.md

@@ -7,9 +7,12 @@
 ```
 /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
 ```
-* Install Java and Spark
+* Install Java 
    * Install Java on OSX following the guide https://java.com/en/download/help/mac_install.xml
-   * Install Spark on OSX http://spark.apache.org/downloads.html
+```
+   export JAVA_HOME=where you unzip your jdk
+   export PATH=$PATH:$JAVA_HOME/bin
+```
 * (Optional) (Mac) Install Python. Python is shipped with MacOS, but you may want to install updates using Homebrew
 ```
 brew install python

ipynb2py.sh

@@ -6,7 +6,6 @@
 # Example:
 # ipynb2py notebooks/neural_networks/rnn
 #########################################
-
 if [ $# -ne "1" ]; then
     echo "Usage: ./nb2script <file-name without extension>"
 else
@@ -17,5 +16,7 @@ else
     jupyter nbconvert --to script $1.tmp.ipynb 
 
     mv $1.tmp.py $1.py
+    sed -i '1i# -*- coding: utf-8 -*-' $1.py
+    sed -i '#!/usr/bin/python' $1.py
     rm $1.tmp.ipynb
 fi 

notebooks/neural_networks/introduction_to_mnist.ipynb

@@ -30,17 +30,23 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Populating the interactive namespace from numpy and matplotlib\n"
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Prepending /usr/local/lib/python2.7/dist-packages/bigdl/share/conf/spark-bigdl.conf to sys.path\n"
      ]
     }
    ],
    "source": [
+    "import matplotlib\n",
+    "matplotlib.use('Agg')\n",
     "# As always, a bit of setup\n",
     "%pylab inline\n",
     "import pandas\n",
     "from bigdl.dataset import mnist\n",
     "from bigdl.util.common import *\n",
-    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pyspark import SparkContext\n",
+    "from matplotlib.pyplot import imshow\n",
+    "sc=SparkContext.getOrCreate(conf=create_spark_conf().setMaster(\"local[4]\").set(\"spark.driver.memory\",\"2g\"))\n",
     "init_engine()"
    ]
   },
@@ -106,15 +112,15 @@
      "data": {
       "image/png": 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HWvyZmZlUFIVXr17lkiVLOHjwYA4ePJgAeP/99/Orr76ioiisrKxkZWWlNrnK39+f06dP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\nHxebd0nIMiF9AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd41f480b50>"
+       "<matplotlib.figure.Figure at 0x7f7294f10c90>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "imshow(np.column_stack(train_images[0:10].reshape(10, 28,28)),cmap='gray'); axis('off')\n",
+    "imshow(np.column_stack(train_images[0:10].reshape(10, 28,28)),cmap='gray'); plt.axis('off')\n",
     "print \"groud true labels: \"\n",
     "print train_labels[0:10]"
    ]

notebooks/neural_networks/linear_regression.ipynb

@@ -23,11 +23,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Populating the interactive namespace from numpy and matplotlib\n"
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Prepending /usr/local/lib/python2.7/dist-packages/bigdl/share/conf/spark-bigdl.conf to sys.path\n"
      ]
     }
    ],
    "source": [
+    "import matplotlib\n",
+    "matplotlib.use('Agg')\n",
     "%pylab inline\n",
     "import pandas\n",
     "import datetime as dt\n",
@@ -37,7 +40,11 @@
     "from bigdl.optim.optimizer import *\n",
     "from bigdl.util.common import *\n",
     "from bigdl.util.common import Sample\n",
+    "import matplotlib.pyplot as plt\n",
     "from bigdl.dataset.transformer import *\n",
+    "from matplotlib.pyplot import imshow\n",
+    "from pyspark import SparkContext\n",
+    "sc=SparkContext.getOrCreate(conf=create_spark_conf().setMaster(\"local[4]\").set(\"spark.driver.memory\",\"2g\"))\n",
     "\n",
     "init_engine()"
    ]
@@ -166,15 +173,15 @@
      "text": [
       "predict predict: \n",
       "\n",
-      "[ 1.48450136]\n",
+      "[ 2.33639312]\n",
       "\n",
-      "[ 3.27808809]\n",
+      "[ 2.0999496]\n",
       "\n",
-      "[ 1.87193513]\n",
+      "[ 1.83889556]\n",
       "\n",
-      "[ 3.40717745]\n",
+      "[ 1.95105672]\n",
       "\n",
-      "[ 4.11920691]\n",
+      "[ 2.58288598]\n",
       "\n"
      ]
     }
@@ -205,7 +212,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "8.19934\n"
+      "8.20632\n"
      ]
     }
    ],