Automatic updates

The Module version of RandomStreams could arrange for the automatic update of certain inputs (such as the random number generators) at the time of make(), so that certain obvious patterns would work:

>>> rs = RandomStreams()
>>> u = rs.uniform(...)
>>> f = theano.function([], u)
>>> assert not numpy.all(f() == f())

Unfortunately, with shared variables this does not work! Function needs to be told which shared variables to update. The current workaround is to do this:

>>> theano.function([], u, updates=rs.updates())

or this:

>>> theano.function([], u, updates=[u.update])

But it is all too easy to forget to do either of these workarounds, and accidentally run a program whose random numbers are the same in every call.

Proposal

Add an optional default_update attribute to Shared variables. This will be consulted by function. If no update expression is given for this variable in the updates list, then this default will be inserted. Note well: a value of None for the default_update means to update with a value of None! To have no default update, make sure that the default_update attribute is not defined.

Add an optional argument to function: no_default_updates. This argument defaults to False, which results in the current semantics. A True value here would mean “ignore all default_update expressions”, and this would be useful for disabling implicit behaviour. A list of shared variables here would mean to ignore the default_update_expressions in these specific variables.

Alternatives

Consider a singleton ‘NOUPDATE’ object that can be used as a pseudo-expression in the update list. This doesn’t introduce a new keyword argument, which makes it slightly more awkward to document in theano.function. Really though, I have no strong feelings between this and the no_updates paramter.