I am making my own linear regression model from scratch
Here is the code
w = torch.tensor(-10.0, requires_grad=True) X = torch.arange(-3, 3.1, 0.1, requires_grad=True).view(-1, 1) F = -3*X Y = f + 0.1 * torch.randn(X.size()) def forward(x): global w y = w*x return y def mse(yhat, y): return torch.mean((y-yhat)**2) learning_rate = 0.1 for epoch in range(1, 11): yhat = forward(x) loss = mse(yhat, y) loss.backward(retain_graph=True) # error occurs here pass
The following exception is thrown after a successful iteration of the dataset
RuntimeError: Trying to backward through the graph a second time, but the buffers have already been freed. Specify retain_graph=True when calling backward the first time.