In [1]:

    

import tensorflow as tf


    

In [2]:

    

graph = tf.get_default_graph()
graph.get_operations()


    

    
Out[2]:





[]

In [3]:

    

input_value = tf.constant(1.0)  # run only once !!!
input_value


    

    
Out[3]:





<tf.Tensor 'Const:0' shape=() dtype=float32>

In [4]:

    

operations = graph.get_operations()
operations


    

    
Out[4]:





[<tf.Operation 'Const' type=Const>]

In [5]:

    

operations[0].node_def


    

    
Out[5]:





name: "Const"
op: "Const"
attr {
  key: "dtype"
  value {
    type: DT_FLOAT
  }
}
attr {
  key: "value"
  value {
    tensor {
      dtype: DT_FLOAT
      tensor_shape {
      }
      float_val: 1.0
    }
  }
}

In [6]:

    

sess = tf.Session()
sess.run(input_value)


    

    
Out[6]:





1.0

In [7]:

    

weight = tf.Variable(0.8)
weight


    

    
Out[7]:





<tf.Variable 'Variable:0' shape=() dtype=float32_ref>

In [8]:

    

for operation in graph.get_operations():
    print(operation.name)


    

    




Const
Variable/initial_value
Variable
Variable/Assign
Variable/read

In [9]:

    

output_value = weight * input_value


    

In [10]:

    

for operation in graph.get_operations():
    print(operation.name)


    

    




Const
Variable/initial_value
Variable
Variable/Assign
Variable/read
mul

In [11]:

    

init = tf.initialize_all_variables() 
sess.run(init)


    

    




WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/util/tf_should_use.py:118: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.
Instructions for updating:
Use `tf.global_variables_initializer` instead.

In [12]:

    

sess.run(output_value)


    

    
Out[12]:





0.8

In [13]:

    

x = tf.constant(1.0, name="input")
w = tf.Variable(0.8, name="weight")
y = tf.multiply(w, x, name="output")


    

In [14]:

    

summary_writer = tf.summary.FileWriter ("log_simple_graph", sess.graph)


    

In [15]:

    

!tensorboard --logdir=log_simple_graph


    

    




W0213 01:00:22.710533 Reloader plugin_event_accumulator.py:300] Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
W0213 01:00:22.711550 Reloader plugin_event_accumulator.py:308] Found more than one metagraph event per run. Overwriting the metagraph with the newest event.
W0213 01:00:22.713455 Reloader plugin_event_accumulator.py:300] Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
TensorBoard 1.5.1 at http://shevkunov:6006 (Press CTRL+C to quit)
^C

In [16]:

    

y_ = tf.constant(0.0)
loss = (y - y_) ** 2


    

In [17]:

    

optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.025)


    

In [18]:

    

gradients_and_vars = optimizer.compute_gradients(loss)


    

In [19]:

    

sess.run(tf.initialize_all_variables())
sess.run(gradients_and_vars[1][0])


    

    
Out[19]:





1.6

In [21]:

    

sess.run(optimizer.apply_gradients(gradients_and_vars))
sess.run(w)


    

    
Out[21]:





0.76

In [24]:

    

train_step = tf.train.GradientDescentOptimizer(learning_rate=0.025).minimize(loss)
for i in xrange(100):
    sess.run(train_step)
sess.run(y)


    

    
Out[24]:





1.5772292e-07

In [30]:

    

sess.run(tf.initialize_all_variables())
summary_y = tf.summary.scalar("output", y)
summary_writer = tf.summary.FileWriter("log_simple_stats")
for i in xrange(100):
    summary_str = sess.run(summary_y)
    summary_writer.add_summary(summary_str, i)
    sess.run(train_step)


    

In [ ]:

    

!tensorboard --logdir=log_simple_stats


    

    




TensorBoard 1.5.1 at http://shevkunov:6006 (Press CTRL+C to quit)
W0213 01:20:19.910441 Thread-1 application.py:273] path /[[_dataImageSrc]] not found, sending 404

In [ ]: