def add_method(self, name,
inputs=None,
outputs=None,
updates=None,
givens=None,
optimizer=None,
):
"""Add a theano function as self.<name>
Parameters
----------
updates - a sequence of `(dest, expr)` pairs of theano variables
When this function is called, it will update each workspace
variable `dest` with the value computed for corresponding symbolic
variable `expr`.
"""
if inputs or outputs or givens:
raise NotImplementedError()
if not updates:
raise NotImplementedError()
ufgraph = UpdateFGraph(updates)
if optimizer:
optimizer = optimizer_from_any(optimizer)
optimizer.apply(ufgraph.fgraph)
cu = CompiledUpdate(ufgraph, self.vals_memo)
return self._add_compiled_update(name, cu)
def optimize_methods(ws, query):
"""Recompile methods so they run faster, if possible.
"""
optimizer = optimizer_from_any(query)
for key, cu in ws.compiled_updates.items():
optimizer.apply(cu.ufgraph.fgraph)
cu_opt = CompiledUpdate(cu.ufgraph, ws.vals_memo)
ws._add_compiled_update(key, cu_opt)
return ws
