What's New in TensorFlow 2.0

Basic operations on Ragged Tensors

Ragged Tensors can be used in a manner similar to regular tensors in many cases. TensorFlow provides over 100 operators that support Ragged Tensors. These operators can be broadly classified as fundamental mathematical operators, array operators, or string operators, among others.

The following code block shows the process of adding two Ragged Tensors:

x = tf.ragged.constant([                         [1, 2, 3, 4],                         [1, 2]                       ])y = tf.ragged.constant([                         [4, 3, 2, 1],                         [5, 6]                       ])print(tf.add(x, y))

This results in the following output:

<tf.RaggedTensor [[5, 5, 5, 5], [6, 8]]>

Another interesting feature is that operator overloading is defined for Ragged Tensors. This means that a programmer can intuitively use operators such as +, -, *, ...