sorry about unclear question. i have read the function you sent to me, thank you. but still a little confusing, what i want is actually like following backward function in torch. https://github.com/torch/nn/blob/master/doc/module.md the initial gradient can be input as the parameter gradOutput. can you help me to figure it out ? how to use this function in theano ? i think it should be possible in theano, right ? thanks a lot.
[gradInput] backward(input, gradOutput) Performs a *backpropagation step* through the module, with respect to the given input. In general this method makes the assumption forward(input) <https://github.com/torch/nn/blob/master/doc/module.md#nn.Module.forward> has been called before, *with the same input*. This is necessary for optimization reasons. If you do not respect this rule, backward() will compute incorrect gradients. In general input and gradOutput and gradInput are Tensors <https://github.com/torch/torch7/blob/master/doc/tensor.md>. However, some special sub-classes like table layers <https://github.com/torch/nn/blob/master/doc/table.md#nn.TableLayers>might expect something else. Please, refer to each module specification for further information. A *backpropagation step* consist in computing two kind of gradients at input given gradOutput (gradients with respect to the output of the module). This function simply performs this task using two function calls: - A function call to updateGradInput(input, gradOutput) <https://github.com/torch/nn/blob/master/doc/module.md#nn.Module.updateGradInput> . - A function call to accGradParameters(input,gradOutput,scale) <https://github.com/torch/nn/blob/master/doc/module.md#nn.Module.accGradParameters> . It is not advised to override this function call in custom classes. It is better to override updateGradInput(input, gradOutput) <https://github.com/torch/nn/blob/master/doc/module.md#nn.Module.updateGradInput> and accGradParameters(input, gradOutput,scale) <https://github.com/torch/nn/blob/master/doc/module.md#nn.Module.accGradParameters> functions. On Thursday, November 3, 2016 at 7:59:53 AM UTC-7, nouiz wrote: > > I'm not sure i understand correctly. Here is the doc about our grad. I'm > pretty sure you can do what you want. Maybe the doc will help you. If not, > can you clarify what you want? > > > http://deeplearning.net/software/theano/library/gradient.html#theano.gradient.grad > > Fred > > On Thu, Nov 3, 2016 at 2:10 AM, <[email protected] <javascript:>> wrote: > >> hello , everyone, if i want to specify an input gradient for an function >> f, how should i implement this in theano ? >> any rely will be appreciated so much... >> >> -- >> >> --- >> 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] <javascript:>. >> 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.
