From https://pytorch.org/docs/stable/_modules/torch/nn/functional.html I see

```
[docs]@weak_script
def dropout(input, p=0.5, training=True, inplace=False):
# type: (Tensor, float, bool, bool) -> Tensor
r"""
During training, randomly zeroes some of the elements of the input
tensor with probability :attr:`p` using samples from a Bernoulli
distribution.
See :class:`~torch.nn.Dropout` for details.
Args:
p: probability of an element to be zeroed. Default: 0.5
training: apply dropout if is ``True``. Default: ``True``
inplace: If set to ``True``, will do this operation in-place. Default: ``False``
"""
if p < 0. or p > 1.:
raise ValueError("dropout probability has to be between 0 and 1, "
"but got {}".format(p))
return (_VF.dropout_(input, p, training)
if inplace
else _VF.dropout(input, p, training))
```

Where is the code for this function? In other words where is `_VF`

object?

I ask because I wanted to confirm if this function is aware of training or not training stage?