want to analyse the intermediary stages of any specific forward function as well. In such a case you can use the
detect_overflow helper function to inject the detector where you want it, for example:
```python
from debug_utils import detect_overflow
class T5LayerFF(nn.Module):
    [...]
def forward(self, hidden_states):
    forwarded_states = self.layer_norm(hidden_states)
    detect_overflow(forwarded_states, "after layer_norm")
    forwarded_states = self.DenseReluDense(forwarded_states)
    detect_overflow(forwarded_states, "after DenseReluDense")
    return hidden_states + self.dropout(forwarded_states)
```
You can see that we added 2 of these and now we track if inf or nan for forwarded_states was detected
somewhere in between.
Actually, the detector already reports these because each of the calls in the example above is a nn.Module, but
