Hi Yang, can you share more about how to draw the graph and label parameter to debug? I met one some problem, but my usage is different: I first trained a modelA, then I use this modelA just as part of an function during training modelB, and modelA should be fixed, but when I try to compile modelB, it dropped this error: DisconnetedInputError: xxxx by a non-differentiable operator: b. But I even don't know where this b occurred, could you give some advice? Thanks.
On Wednesday, January 20, 2016 at 9:24:21 AM UTC+8, Yang Xiang wrote: > > Thanks Daniel, > > I tried to draw out the whole graph and label all the parameters along the > path, and finally fixed the problem. The name of one parameter (when I > copied the paramters from the forward RNN to backward) was misspelled. > > Finally I still have no idea about why the NIL params for grad would also > caused this problem, and I suggest this warning (exception) should be threw > along with the name of the disconnected paramter but not only some type > information. And one thing more I learned is that drawing the graph and > labeling the parameters is a good way for debugging this disconnect error. > > Yang > > 在 2016年1月17日星期日 UTC+8下午9:53:53，Daniel Renshaw写道： >> >> Are you saying you have code of this form: >> >> import theano.tensor as tt >> >> x = tt.matrix() >> c = tt.sum(2 * x) >> gs = tt.grad(c, []) >> >> i.e. an attempt to compute the gradient of some cost c with respect to... >> nothing, is generating the exception whose details you posted? >> >> If so we'll probably need to see what the cost computation is, can you >> share more code? Have you been able to reproduce the problem with simple >> code that can be executed without any external dependencies? >> >> Daniel >> >> >> >> On 16 January 2016 at 15:02, Yang Xiang <[email protected]> wrote: >> >>> Hi all, >>> >>> I encountered theano.gradient.DisconnectedInputError when I wrote my >>> code for an end-to-end process. I have a series of parameters to update. In >>> order to check which parameter caused the disconnect error, I removed them >>> from the function's parameters one by one. But after I removed all the >>> parameters (params=[]), this error was still there? What does this case >>> mean? >>> >>> The error report stated: theano.gradient.DisconnectedInputError: grad >>> method was asked to compute the gradient with respect to a variable that is >>> not part of the computational graph of the cost, or is used only by a >>> non-differentiable operator: <TensorType(float64, 4D)> >>> >>> Could anyone help? >>> >>> Thanks. >>> >>> Yang >>> >>> -- >>> >>> --- >>> You received this message because you are subscribed to the Google >>> Groups "theano-users" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected]. >>> For more options, visit https://groups.google.com/d/optout. >>> >> >> -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
