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Tensorflow Note - 2

Prerequisites

You are using Windows 7 or higher version
You are using Anaconda to setup the environment

Install Anaconda

Anaconda® is a package manager, an environment manager, a Python/R data science distribution, and a collection of over 1,500+ open source packages. Anaconda is free and easy to install, and it offers free community support.

Please download Anaconda from the official site

Create tensorflow virtualenv with python 3.5

Anaconda uses python 3.6 by default. Tensorflow only supports python 3.5.

cd /path/to/envs conda create -n tensorflow

Install tensorflow

activate tensorflow
## For CPU
pip install --ignore-installed --upgrade \
    https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.1.0-cp35-cp35m-win_amd64.whl

## Or for GPU
pip install --ignore-installed --upgrade \
    https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.1.0-cp35-cp35m-win_amd64.whl

Use sample code to test Tensorflow

Save code below to file test.py

import numpy as np
import tensorflow as tf

## Model parameters
W = tf.Variable([.3], tf.float32)
b = tf.Variable([-.3], tf.float32)
## Model input and output
x = tf.placeholder(tf.float32)
linear_model = W * x + b
y = tf.placeholder(tf.float32)
## loss
loss = tf.reduce_sum(tf.square(linear_model - y)) ## sum of the squares
## optimizer
optimizer = tf.train.GradientDescentOptimizer(0.01)
train = optimizer.minimize(loss)
## training data
x_train = [1,2,3,4]
y_train = [0,-1,-2,-3]
## training loop
init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init) ## reset values to wrong
for i in range(1000):
sess.run(train, {x:x_train, y:y_train})

## evaluate training accuracy
curr_W, curr_b, curr_loss  = sess.run([W, b, loss], {x:x_train, y:y_train})
print("W: %s b: %s loss: %s"%(curr_W, curr_b, curr_loss))

Test with tensorflow-gpu (GPU enabled)

activate tensorflow
cd /ws/python/tf
python3 test.py

## You will probably see the result as follow 
## ....
## name: GeForce GTX 850M
## major: 5 minor: 0 memoryClockRate (GHz) 0.9015
## pciBusID 0000:0a:00.0
## Total memory: 3.95GiB
## Free memory: 3.58GiB
## 2017-04-25 10:25:59.640621: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 
## 2017-04-25 10:25:59.640626: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0:   Y 
## 2017-04-25 10:25:59.640640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] 
##    Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 850M, pci ## bus id: 0000:0a:00.0)
## W: [-0.9999969] b: [ 0.99999082] loss: 5.69997e-11