Creating Parameters
Learn about the different methods of creating parameters.
We'll cover the following...
Tensors requiring gradients
What distinguishes a tensor used for training data from a tensor used as a trainable parameter/weight?
The latter requires the computation of its gradients, so we can update their values (the parameters’ values, that is). That is what the requires_grad=True argument is good for. It tells PyTorch to compute gradients for us.
A tensor for a learnable parameter requires a gradient!
You may be tempted to create a simple tensor for a parameter and send it to your chosen device later on; this was similarly done with our data, right? Not so fast.
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In the next few segments, you will be presented with four chunks of code that show different attempts at creating parameters.
The first three attempts are shown to build up a solution. The firs ...
First attempt
The ...