How can I assign/update subset of tensor shared variable in Theano?

Question

When compiling a function in theano, a shared variable(say X) can be updated by specifying updates=[(X, new_value)]. Now I am trying to update only subset of a shared variable:

from theano import tensor as T from theano import function import numpy  X = T.shared(numpy.array([0,1,2,3,4])) Y = T.vector() f = function([Y], updates=[(X[2:4], Y)] # error occur:                                         # 'update target must                                          # be a SharedVariable' 

The codes will raise a error "update target must be a SharedVariable", I guess that means update targets can't be non-shared variables. So is there any way to compile a function to just udpate subset of shared variables?

Answer 1

Use set_subtensor or inc_subtensor:

from theano import tensor as T from theano import function, shared import numpy  X = shared(numpy.array([0,1,2,3,4])) Y = T.vector() X_update = (X, T.set_subtensor(X[2:4], Y)) f = function([Y], updates=[X_update]) f([100,10]) print X.get_value() # [0 1 100 10 4] 

There's now a page about this in the Theano FAQ: http://deeplearning.net/software/theano/tutorial/faq_tutorial.html