cflamant

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cflamant

## Example training loop from within a class which contains
## a PyTorch nn.Module() under the variable self.net()

optimizer = optim.SGD(self.net.parameters(), lr=0.001)
train_losses = []
with tqdm.trange(num_batch) as batches:
  for b in batches:
    x = self.getdata()
    # Call network for forward pass
    losses = self.net(x)

cflamant

"""
Code to demonstrate dynamically creating subclasses for a
superclass that is not known before execution.

General idea: you want to make a subclass that is a baby animal,
but you don't know whether it will be a Human or Sheep (or possibly
another animal from a different module) until the code is run.
By creating the subclass dynamically (using the "type" function),
you can avoid writing a separate subclass for each superclass possibility.

cflamant

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