# create a rank1 tensor object

import tensorflow as tf

mystr = tf.Variable(["Hello"], tf.string)

cool_numbers = tf.Variable([3.14159, 2.71828], tf.float32)

first_primes = tf.Variable([2, 3, 5, 7, 11], tf.int32)

its_very_complicated = tf.Variable([12.3 - 4.85j, 7.5 - 6.23j], tf.complex64)

init = tf.global_variables_initializer()

sess = tf.Session()

sess.run(init)

print(sess.run(mystr))

print(sess.run(cool_numbers))

print(sess.run(first_primes))

print(sess.run(its_very_complicated))

2018-02-16 21:31:32.599557: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

[b'Hello']

[ 3.14159012  2.71828008]

[ 2  3  5  7 11]

[ 12.3-4.85j   7.5-6.23j]

# create rank2 tensor

import tensorflow as tf

mymat = tf.Variable([[7], [11]], tf.int16)

myxor = tf.Variable([[False, True], [True, False]], tf.bool)

linear_squares = tf.Variable([[4], [9], [16], [25]], tf.int32)

squarish_squares = tf.Variable([ [4, 9], [16, 25] ], tf.int32)

rank_of_squares = tf.rank(linear_squares)

mymatC = tf.Variable([[7], [11]], tf.int32)

init = tf.global_variables_initializer()

sess = tf.Session()

sess.run(init)

print(sess.run(rank_of_squares))

2018-02-16 21:33:53.407399: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

2

# create higher rank tensors ,

# consist of an n-dimensional array

import tensorflow as tf

my_image = tf.zeros([10, 299, 299, 3])

# Getting a tf.Tensor object's rank

r = tf.rank(my_image)

init = tf.global_variables_initializer()

sess = tf.Session()

sess.run(init)

print(sess.run(r))

2018-02-16 21:34:57.278721: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

4