Tensorflow python : Accessing individual elements in a tensor

There are two main ways to access subsets of the elements in a tensor, either of which should work for your example.

1. Use the indexing operator (based on tf.slice()) to extract a contiguous slice from the tensor.

   input = tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
   
   output = input[0, :]
   print sess.run(output)  # ==> [1 2 3]
   

   The indexing operator supports many of the same slice specifications as NumPy does.

2. Use the tf.gather() op to select a non-contiguous slice from the tensor.

   input = tf.constant([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
   
   output = tf.gather(input, 0)
   print sess.run(output)  # ==> [1 2 3]
   
   output = tf.gather(input, [0, 2])
   print sess.run(output)  # ==> [[1 2 3] [7 8 9]]
   

   Note that tf.gather() only allows you to select whole slices in the 0th dimension (whole rows in the example of a matrix), so you may need to tf.reshape() or tf.transpose() your input to obtain the appropriate elements.