Reduce the use of SymPy lambdify (#579)

* evaluate SymPy parameter without lambdify

* clear linecache after use of lambdify

* comments

* formatting

* changelog, linting

.github/CHANGELOG.md

@@ -13,6 +13,10 @@
 
 <h3>Bug fixes</h3>
 
+* Fixed an unexpected behaviour that can result in increasing memory usage due
+  to ``sympy.lambdify`` caching too much data using ``linecache``.
+  [(#579)](https://github.com/XanaduAI/strawberryfields/pull/579)
+
 <h3>Documentation</h3>
 
 * References to the ``simulon`` simulator target have been rewritten to
@@ -25,7 +29,7 @@
 
 This release contains contributions from (in alphabetical order):
 
-Aaron Robertson, Jeremy Swinarton.
+Aaron Robertson, Jeremy Swinarton, Antal Száva.
 
 # Release 0.18.0 (current release)
 

strawberryfields/parameters.py

@@ -96,6 +96,7 @@
 import collections.abc
 import functools
 import types
+import linecache
 
 import numpy as np
 import sympy
@@ -191,14 +192,26 @@ def do_evaluate(p):
 
         # using lambdify we can also substitute np.ndarrays and tf.Tensors for the atoms
         atoms = list(p.atoms(MeasuredParameter, FreeParameter))
+
+        if not atoms:
+            # If there are not atomic values, we just convert to elementary
+            # Python types
+            return float(p) if p.is_real else complex(p)
+
         # evaluate the atoms of the expression
         vals = [k._eval_evalf(None) for k in atoms]
         # use the tensorflow printer if any of the symbolic parameter values are TF objects
         # (we do it like this to avoid importing tensorflow if it's not needed)
         is_tf = (type(v).__module__.startswith("tensorflow") for v in vals)
         printer = "tensorflow" if any(is_tf) else "numpy"
+
         func = sympy.lambdify(atoms, p, printer)
 
+        # sympy.lambdify caches data using linecache, if called many times this
+        # can make up for a lot of memory used. We clear the cache here to
+        # avoid that.
+        linecache.clearcache()
+
         if dtype is not None:
             # cast the input values
             if printer == "tensorflow":