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Ensure TemplateOptimization returns native-symbolic objects
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`TemplateOptimization` currently uses Sympy internally to get access to
solvers that have no equivalent in Symengine.  Previously, it then did
not convert the solutions to its equations back into Symengine format
(if appropriate) before passing them on to `ParameterExpression`, which
could lead to different assumptions about the type of the contained
objects and bugs if `ParameterExpression` attempted to use
Symengine-specific forms of methods on Sympy objects.
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jakelishman committed Oct 25, 2023
1 parent 594ae55 commit 7e70ef2
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Showing 3 changed files with 67 additions and 13 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
from qiskit.dagcircuit.dagcircuit import DAGCircuit
from qiskit.dagcircuit.dagdependency import DAGDependency
from qiskit.converters.dagdependency_to_dag import dagdependency_to_dag
from qiskit.utils import optionals as _optionals


class SubstitutionConfig:
Expand Down Expand Up @@ -496,6 +497,15 @@ def _attempt_bind(self, template_sublist, circuit_sublist):
import sympy as sym
from sympy.parsing.sympy_parser import parse_expr

if _optionals.HAS_SYMENGINE:
import symengine

# Converts Sympy expressions to Symengine ones.
to_native_symbolic = symengine.sympify
else:
# Our native form is sympy, so we don't need to do anything.
to_native_symbolic = lambda x: x

circuit_params, template_params = [], []
# Set of all parameter names that are present in the circuits to be optimised.
circuit_params_set = set()
Expand Down Expand Up @@ -555,7 +565,7 @@ def dummy_parameter():
node.op.params = sub_node_params

# Create the fake binding dict and check
equations, circ_dict, temp_symbols, sol, fake_bind = [], {}, {}, {}, {}
equations, circ_dict, temp_symbols = [], {}, {}
for circuit_param, template_param in zip(circuit_params, template_params):
if isinstance(template_param, ParameterExpression):
if isinstance(circuit_param, ParameterExpression):
Expand All @@ -577,19 +587,18 @@ def dummy_parameter():
if not temp_symbols:
return template_dag_dep

# Check compatibility by solving the resulting equation
sym_sol = sym.solve(equations, set(temp_symbols.values()))
for key in sym_sol:
try:
sol[str(key)] = ParameterExpression(circ_dict, sym_sol[key])
except TypeError:
return None

if not sol:
# Check compatibility by solving the resulting equation. `dict=True` (surprisingly) forces
# the output to always be a list, even if there's exactly one solution.
sym_sol = sym.solve(equations, set(temp_symbols.values()), dict=True)
if not sym_sol:
# No solutions.
return None

for key in temp_symbols:
fake_bind[key] = sol[str(key)]
# If there's multiple solutions, arbitrarily pick the first one.
sol = {
param.name: ParameterExpression(circ_dict, to_native_symbolic(expr))
for param, expr in sym_sol[0].items()
}
fake_bind = {key: sol[key.name] for key in temp_symbols}

for node in template_dag_dep.get_nodes():
bound_params = []
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@@ -0,0 +1,8 @@
---
fixes:
- |
The :class:`.TemplateOptimization` pass will now return parametric expressions using the native
symbolic expression format of :class:`.ParameterExpression`, rather than always using Sympy.
For most supported platforms, this means that the expressions will be Symengine objects.
Previously, the pass could return mismatched objects, which could lead to later failures in
parameter-handling code.
37 changes: 37 additions & 0 deletions test/python/transpiler/test_template_matching.py
Original file line number Diff line number Diff line change
Expand Up @@ -344,6 +344,43 @@ def count_cx(qc):
# however these are equivalent if the operators are the same
self.assertTrue(Operator(circuit_in).equiv(circuit_out))

def test_output_symbolic_library_equal(self):
"""Test that the template matcher returns parameter expressions that use the same symbolic
library as the default; it should not coerce everything to Sympy when playing with the
`ParameterExpression` internals."""

a, b = Parameter("a"), Parameter("b")

template = QuantumCircuit(1)
template.p(a, 0)
template.p(-a, 0)
template.rz(a, 0)
template.rz(-a, 0)

circuit = QuantumCircuit(1)
circuit.p(-b, 0)
circuit.p(b, 0)

pass_ = TemplateOptimization(template_list=[template], user_cost_dict={"p": 100, "rz": 1})
out = pass_(circuit)

expected = QuantumCircuit(1)
expected.rz(-b, 0)
expected.rz(b, 0)
self.assertEqual(out, expected)

def symbolic_library(expr):
"""Get the symbolic library of the expression - 'sympy' or 'symengine'."""
return type(expr._symbol_expr).__module__.split(".")[0]

out_exprs = [expr for instruction in out.data for expr in instruction.operation.params]
self.assertEqual(
[symbolic_library(b)] * len(out_exprs), [symbolic_library(expr) for expr in out_exprs]
)

# Assert that the result still works with parametric assignment.
self.assertEqual(out.assign_parameters({b: 1.5}), expected.assign_parameters({b: 1.5}))

def test_optimizer_does_not_replace_unbound_partial_match(self):
"""
Test that partial matches with parameters will not raise errors.
Expand Down

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