Default value initialization

There are many cases where we need to initialize torch tensors to default values. Here, we create three 2 x 3 tensors, filling them with zeros, ones, and random floating point numbers:

An important point to consider when we are initializing random arrays is the so-called seed of reproducibility. See what happens when you run the preceding code several times. You get a different array of random numbers each time. Often in machine learning, we need to be able to reproduce results. We can achieve this by using a random seed. This is demonstrated in the following code:

Notice that when you run this code many times, the tensor values stay the same. If you remove the seed by deleting the first line, the tensor values will be different each time the code is run. It does not matter what number you use to seed the random number generator, as long as it is consistently, achieves reproducible results.