https://github.com/ashwanikumar04/tensorflow-handson
Tensor flow handson
https://github.com/ashwanikumar04/tensorflow-handson
tensorflow
Last synced: 2 months ago
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Tensor flow handson
- Host: GitHub
- URL: https://github.com/ashwanikumar04/tensorflow-handson
- Owner: ashwanikumar04
- License: mit
- Created: 2018-03-18T09:55:02.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-03-22T14:40:55.000Z (over 8 years ago)
- Last Synced: 2024-12-30T07:44:06.014Z (over 1 year ago)
- Topics: tensorflow
- Language: Jupyter Notebook
- Size: 4.88 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## Some handson on Tensor flow.
## Hello Tensorflow
```python
import tensorflow as tf
hello_constant = tf.constant('Hello Constant')
with tf.Session() as sess:
output = sess.run(hello_constant)
print(output)
```
b'Hello Constant'
# Input
```python
x = tf.placeholder(tf.string)
with tf.Session() as sess:
output=sess.run(x,feed_dict={x:'Hello World'})
print(output)
```
Hello World
```python
x = tf.placeholder(tf.int32)
with tf.Session() as sess:
output=sess.run(x,feed_dict={x:123})
print(output)
```
123
```python
# TODO: Convert the following to TensorFlow:
x = tf.constant(10)
y = tf.constant(2)
z = tf.subtract(tf.divide(x,y),tf.cast(tf.constant(1),tf.float64))
with tf.Session() as sess:
output=sess.run(z)
print(output)
```
4.0
```python
node1 = tf.constant(2)
node2 = tf.constant(3)
with tf.Session() as sess:
node3 = sess.run(node1+node2)
print(node3)
```
5
## TensorBoard
```python
import tensorflow as tf
a = tf.constant(4,name='node_a')
b = tf.constant(5,name='node_b')
c = tf.multiply(a,b,name='multiply_c')
d = tf.add(a,b,name='add_d')
e = tf.add(c,d,name='add_e')
sess = tf.Session()
output = sess.run(e)
writer = tf.summary.FileWriter('./graph1',sess.graph)
writer.close()
sess.close()
```
## Run Tensorboard
```
tensorboard --logdir=graph1/
```
```
Starting TensorBoard b'47' at http://0.0.0.0:6006
(Press CTRL+C to quit)
```
# Linear Model
```python
import tensorflow as tf
W = tf.Variable([.3],tf.float32)
b = tf.Variable([-.3],tf.float32)
x = tf.placeholder(tf.float32)
linear_model = W*x+b
init = tf.global_variables_initializer()
y = tf.placeholder(tf.float32)
squared_deltas = tf.square(linear_model-y)
loss = tf.reduce_sum(squared_deltas)
optmizer = tf.train.GradientDescentOptimizer(0.01)
train = optmizer.minimize(loss)
with tf.Session() as sess:
sess.run(init)
print(sess.run(linear_model,{x:[1,2,3,4]}))
print(sess.run(loss,{x:[1,2,3,4],y:[0,-1,-2,-3]}))
print('Training')
with tf.Session() as sess:
sess.run(init)
for i in range(1000):
sess.run(train,{x:[1,2,3,4],y:[0,-1,-2,-3]})
print(sess.run([W,b]))
```
[ 0. 0.30000001 0.60000002 0.90000004]
23.66
Training
[array([-0.9999969], dtype=float32), array([ 0.99999082], dtype=float32)]