No. On the GPU, we have our own allocator on top of cuda malloc. On the CPU, we use NumPy allocator. So if you find a way to change numpy allocator, then you will be good. There was discussion of letting this possible. I don't know if this was finished or not.
We allow to keep all allocated memory in the graph to lower allocation overhead via the Theano flag: allow_gc=False. This will raise significatively the CPU memory usage. Fred On Tue, Jan 31, 2017 at 6:52 PM Михаил Ширяев <[email protected]> wrote: > Hi, > Is there any way to set custom allocator for tensor's allocation from user > script? > > -- > > --- > 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.
