# importing packages
import tensorflow.compat.v1 as tf
  
# disabling eager mode
tf.compat.v1.disable_eager_execution()
  
# creating a placeholder
a = tf.placeholder(tf.float32, None)
  
# creating an operation
b = a + 10
  
# creating a session
with tf.Session() as session:
    
    # feeding data in the placeholder
    operation_res = session.run(b, feed_dict={a: [10, 20, 30, 40]})
    print("after executing the operation: " + str(operation_res))

after executing the operation: [20. 30. 40. 50.]

# importing packages
import tensorflow.compat.v1 as tf
  
# disabling eager mode
tf.compat.v1.disable_eager_execution()
  
# creating a tensorflow graph
graph = tf.Graph()
with graph.as_default():
    
    # creating a placeholder
    a = tf.placeholder(tf.float64, shape=(3, 3), name='tensor1')
      
    # creating an operation
    b = a ** 2
  
# array1 will be fed into 'a'
array1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
  
# Creating a session, and running the graph
with tf.Session(graph=graph) as session:
      
    # run the session until it reaches node b,
    # then input an array of values into a
    operation_res = session.run(b, feed_dict={a: array1})
    print("after executing the operation: ")
    print(operation_res)

after executing the operation: 
[[ 1.  4.  9.]
 [16. 25. 36.]
 [49. 64. 81.]]