23.09.2020 · alpha = nn.Parameter(torch.ones(1)*5) ... def forward(self, x): ... x = x * alpha return x This should work because of the BROADCASTING SEMANTICS of PyTorch. But I wonder why or why not the following be used, def __ini... Best way to define a scalar using nn.Parameter in Pytorch vision mohit117(Mohit Lamba)
A PyTorch Variable is a wrapper around a PyTorch Tensor, and represents a node in a computational graph. If x is a Variable then x.data is a Tensor giving ...
A kind of Tensor that is to be considered a module parameter. ... loss is a Scalar representing the computed negative log likelihood loss. Return type:.
06.02.2020 · No, you should use the parameter in your model code: scalar = nn.Parameter(torch.randn(shape)). Pytorch supports scalar multiplication like this: (B,C,H,W)*(C,H,W). 1 Like. Niki (Niki) February 6, 2020, 4:03pm #7. Thank you, @G.M. How should I apply this in optimizer? the current one is ...
Parameter¶ class torch.nn.parameter. Parameter (data = None, requires_grad = True) [source] ¶. 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 …
09.01.2021 · dear all, I am a rookie with pytorch. I am trying to add a parameter, something like a scalar, to a neural network with I previously defined and added to the optimizer optimizer = torch.optim.Adam(model_g.parameters(), lr=learning_rate) a = torch.tensor([1.0]).type(Tensor) optimizer.add_param_group({'params': a}) then I do: # Forward pass g = model_g(input) # …
19.07.2019 · I am new to pytorch. I want to know how to declare a scalar as a parameter. I am wondering what's the difference between the following two ways? x = torch.randn(1,1, requires_grad=True) and tens...