#!/usr/bin/env python
# coding: utf-8

# # Operations on a Computational Graph
# 
# We start by loading the necessary libraries and resetting the computational graph.

# In[2]:


import os
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.python.framework import ops
ops.reset_default_graph()


# ### Start a graph session

# In[3]:


sess = tf.Session()


# ### Create tensors

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# Create data to feed in the placeholder
x_vals = np.array([1., 3., 5., 7., 9.])

# Create the TensorFlow Placceholder
x_data = tf.placeholder(tf.float32)

# Constant for multilication
m = tf.constant(3.)


# We loop through the input values and print out the multiplication operation for each input.

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# Multiplication
prod = tf.multiply(x_data, m)
for x_val in x_vals:
    print(sess.run(prod, feed_dict={x_data: x_val}))


# ### Output graph to Tensorboard

# In[6]:


merged = tf.summary.merge_all(key='summaries')
if not os.path.exists('tensorboard_logs/'):
    os.makedirs('tensorboard_logs/')

my_writer = tf.summary.FileWriter('tensorboard_logs/', sess.graph)


# ![Operations on a Graph](https://github.com/nfmcclure/tensorflow_cookbook/raw/master/02_TensorFlow_Way/images/01_Operations_on_a_Graph.png)

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