In [1]:

    

import numpy as np
import tensorflow as tf
print ("PACKAGES LOADED")


    

    




PACKAGES LOADED

In [2]:

    

sess = tf.Session()
print ("OPEN SESSION")


    

    




OPEN SESSION

In [3]:

    

def print_tf(x):
    print("TYPE IS\n %s" % (type(x)))
    print("VALUE IS\n %s" % (x))
hello = tf.constant("HELLO. IT'S ME. ")
print_tf(hello)


    

    




TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("Const:0", shape=(), dtype=string)

In [4]:

    

hello_out = sess.run(hello)
print_tf(hello_out)


    

    




TYPE IS
 <type 'str'>
VALUE IS
 HELLO. IT'S ME. 

In [5]:

    

a = tf.constant(1.5)
b = tf.constant(2.5)
print_tf(a)
print_tf(b)


    

    




TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("Const_1:0", shape=(), dtype=float32)
TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("Const_2:0", shape=(), dtype=float32)

In [6]:

    

a_out = sess.run(a)
b_out = sess.run(b)
print_tf(a_out)
print_tf(b_out)


    

    




TYPE IS
 <type 'numpy.float32'>
VALUE IS
 1.5
TYPE IS
 <type 'numpy.float32'>
VALUE IS
 2.5

In [7]:

    

a_plus_b = tf.add(a, b)
print_tf(a_plus_b)


    

    




TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("Add:0", shape=(), dtype=float32)

In [8]:

    

a_plus_b_out = sess.run(a_plus_b)
print_tf(a_plus_b_out)


    

    




TYPE IS
 <type 'numpy.float32'>
VALUE IS
 4.0

In [9]:

    

a_mul_b = tf.mul(a, b)
a_mul_b_out = sess.run(a_mul_b)
print_tf(a_mul_b_out)


    

    




TYPE IS
 <type 'numpy.float32'>
VALUE IS
 3.75

In [10]:

    

weight = tf.Variable(tf.random_normal([5, 2], stddev=0.1))
print_tf(weight)


    

    




TYPE IS
 <class 'tensorflow.python.ops.variables.Variable'>
VALUE IS
 <tensorflow.python.ops.variables.Variable object at 0x7ff2bc04c050>

In [11]:

    

weight_out = sess.run(weight)
print_tf(weight_out)


    

    




---------------------------------------------------------------------------
FailedPreconditionError                   Traceback (most recent call last)
<ipython-input-11-e453db2b7ada> in <module>()
----> 1 weight_out = sess.run(weight)
      2 print_tf(weight_out)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
    338     try:
    339       result = self._run(None, fetches, feed_dict, options_ptr,
--> 340                          run_metadata_ptr)
    341       if run_metadata:
    342         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
    562     try:
    563       results = self._do_run(handle, target_list, unique_fetches,
--> 564                              feed_dict_string, options, run_metadata)
    565     finally:
    566       # The movers are no longer used. Delete them.

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
    635     if handle is None:
    636       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
--> 637                            target_list, options, run_metadata)
    638     else:
    639       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
    657       # pylint: disable=protected-access
    658       raise errors._make_specific_exception(node_def, op, error_message,
--> 659                                             e.code)
    660       # pylint: enable=protected-access
    661 

FailedPreconditionError: Attempting to use uninitialized value Variable
	 [[Node: Variable/_14 = _Send[T=DT_FLOAT, client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_25_Variable", _device="/job:localhost/replica:0/task:0/gpu:0"](Variable)]]
	 [[Node: Variable/_15 = _Recv[_start_time=0, client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_25_Variable", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

In [12]:

    

init = tf.initialize_all_variables()
sess.run(init)
print ("INITIALIZING ALL VARIALBES")


    

    




INITIALIZING ALL VARIALBES

In [13]:

    

weight_out = sess.run(weight)
print_tf(weight_out)


    

    




TYPE IS
 <type 'numpy.ndarray'>
VALUE IS
 [[ 0.08847231 -0.08040368]
 [-0.00344782 -0.32673332]
 [ 0.10427399 -0.12950435]
 [ 0.19032514 -0.1323577 ]
 [-0.00949183 -0.10073283]]

In [15]:

    

x = tf.placeholder(tf.float32, [None, 5])
print_tf(x)


    

    




TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("Placeholder:0", shape=(?, 5), dtype=float32)

In [18]:

    

oper = tf.matmul(x, weight)
print_tf(oper)


    

    




TYPE IS
 <class 'tensorflow.python.framework.ops.Tensor'>
VALUE IS
 Tensor("MatMul_1:0", shape=(?, 2), dtype=float32)

In [21]:

    

data = np.random.rand(1, 5)
oper_out = sess.run(oper, feed_dict={x: data})
print_tf(oper_out)


    

    




TYPE IS
 <type 'numpy.ndarray'>
VALUE IS
 [[ 0.15189362 -0.18824303]]

In [22]:

    

data = np.random.rand(2, 5)
oper_out = sess.run(oper, feed_dict={x: data})
print_tf(oper_out)


    

    




TYPE IS
 <type 'numpy.ndarray'>
VALUE IS
 [[ 0.25157502 -0.50201333]
 [ 0.11929326 -0.4199847 ]]