A kind of Tensor that is to be considered a module parameter.
Tensorsubclasses, that have a very special property when used with
Modules - when they’re assigned as Module attributes they are automatically added to the list of its parameters, and will appear e.g. in
parameters()iterator. Assigning a Tensor doesn’t have such effect. This is because one might want to cache some temporary state, like last hidden state of the RNN, in the model. If there was no such class as
Parameter, these temporaries would get registered too.
data (Tensor) – parameter tensor.
requires_grad (bool, optional) – if the parameter requires gradient. See Locally disabling gradient computation for more details. Default: True