A kind of Tensor that is to be considered a module parameter.
Parameters are Tensor subclasses, that have a very special property when used with Module s - 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. Note that the torch.no_grad() context does NOT affect the default behavior of Parameter creation–the Parameter will still have requires_grad=True in no_grad mode. See Locally disabling gradient computation for more details. Default: True
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