benchmark: Followup and modify benchmarks

benchmarks/purefock_clements_interferometer_comparison_benchmark.py

@@ -71,7 +71,8 @@ def func():
                 )
                 pq.Q(*operation["modes"]) | pq.Beamsplitter(operation["params"][0], 0.0)
 
-                pq.Q() | pq.Phaseshifter(np.angle(decomposition.diagonals))
+            for i, angle in enumerate(np.angle(decomposition.diagonals)):
+                pq.Q(i) | pq.Phaseshifter(angle)
 
             for operation in reversed(decomposition.direct_operations):
                 pq.Q(*operation["modes"]) | pq.Beamsplitter(

benchmarks/purefock_general_benchmark.py

@@ -41,11 +41,17 @@ def xi():
     return 0.3
 
 
-parameters = [(d, unitary_group.rvs(d)) for d in range(3, 7)]
+@pytest.fixture
+def cutoff():
+    return 15
+
+
+@pytest.fixture
+def d():
+    return 5
 
 
-@pytest.mark.parametrize("d, interferometer", parameters)
-def piquasso_benchmark(benchmark, d, interferometer, r, alpha, xi):
+def piquasso_benchmark(benchmark, cutoff, r, alpha, xi, d):
     @benchmark
     def func():
         with pq.Program() as program:
@@ -54,21 +60,20 @@ def func():
             for i in range(d):
                 pq.Q(i) | pq.Displacement(r=alpha) | pq.Squeezing(r)
 
-            pq.Q(all) | pq.Interferometer(interferometer)
+            pq.Q(all) | pq.Interferometer(unitary_group.rvs(d))
 
             for i in range(d):
                 pq.Q(i) | pq.Kerr(xi)
 
-        simulator_fock = pq.PureFockSimulator(d=d, config=pq.Config(cutoff=d))
+        simulator_fock = pq.PureFockSimulator(d=d, config=pq.Config(cutoff=cutoff))
 
         simulator_fock.execute(program)
 
 
-@pytest.mark.parametrize("d, interferometer", parameters)
-def strawberryfields_benchmark(benchmark, d, interferometer, r, alpha, xi):
+def strawberryfields_benchmark(benchmark, cutoff, r, alpha, xi, d):
     @benchmark
     def func():
-        eng = sf.Engine(backend="fock", backend_options={"cutoff_dim": d})
+        eng = sf.Engine(backend="fock", backend_options={"cutoff_dim": cutoff})
 
         circuit = sf.Program(d)
 
@@ -77,7 +82,7 @@ def func():
                 sf.ops.Dgate(alpha) | q[i]
                 sf.ops.Sgate(r) | q[i]
 
-            sf.ops.Interferometer(interferometer) | tuple(q[i] for i in range(d))
+            sf.ops.Interferometer(unitary_group.rvs(d)) | tuple(q[i] for i in range(d))
 
             for i in range(d):
                 sf.ops.Kgate(xi) | q[i]

scripts/profile_cvnn_layer.py

@@ -20,6 +20,9 @@
 import numpy as np
 
 
+PROFILE = False
+
+
 def create_layer_parameters(d: int):
     number_of_beamsplitters: int
     if d % 2 == 0:
@@ -53,8 +56,8 @@ def create_layer_parameters(d: int):
 
 
 input = 0.01
-d = 8
-cutoff = 8
+d = 2
+cutoff = 10
 
 target_state_vector = np.zeros(cutoff_cardinality(cutoff=cutoff, d=d), dtype=complex)
 target_state_vector[1] = 1.0
@@ -64,11 +67,17 @@ def create_layer_parameters(d: int):
 
 parameters = create_layer_parameters(d)
 
+if PROFILE:
+    profiler_options = tf.profiler.experimental.ProfilerOptions(python_tracer_level=1)
+    tf.profiler.experimental.start("logdir", options=profiler_options)
+
+
 with tf.GradientTape() as tape:
     with pq.Program() as program:
         pq.Q(all) | pq.Vacuum()
 
-        pq.Q(all) | pq.Displacement(r=input)
+        for mode in range(d):
+            pq.Q(mode) | pq.Displacement(r=input)
 
         i = 0
         for col in range(d):
@@ -87,7 +96,8 @@ def create_layer_parameters(d: int):
         for i in range(d - 1):
             pq.Q(i) | pq.Phaseshifter(parameters["phis_1"][i])
 
-        pq.Q(all) | pq.Squeezing(parameters["squeezings"])
+        for mode, r in enumerate(parameters["squeezings"]):
+            pq.Q(mode) | pq.Squeezing(r)
 
         i = 0
         for col in range(d):
@@ -106,8 +116,11 @@ def create_layer_parameters(d: int):
         for i in range(d - 1):
             pq.Q(i) | pq.Phaseshifter(parameters["phis_2"][i])
 
-        pq.Q(all) | pq.Displacement(r=parameters["displacements"])
-        pq.Q(all) | pq.Kerr(parameters["kappas"])
+        for mode, r in enumerate(parameters["displacements"]):
+            pq.Q(mode) | pq.Displacement(r=r)
+
+        for mode, xi in enumerate(parameters["kappas"]):
+            pq.Q(mode) | pq.Kerr(xi=xi)
 
     start_time = time.time()
     state = simulator.execute(program).state
@@ -118,12 +131,6 @@ def create_layer_parameters(d: int):
     cost = tf.reduce_sum(tf.abs(target_state_vector - state_vector))
 
 
-profiler_options = tf.profiler.experimental.ProfilerOptions(
-    host_tracer_level=3, python_tracer_level=3, device_tracer_level=3
-)
-
-# tf.profiler.experimental.start("logdir", options=profiler_options)
-
 flattened_parameters = (
     parameters["thetas_1"]
     + parameters["phis_1"]
@@ -137,7 +144,8 @@ def create_layer_parameters(d: int):
 start_time = time.time()
 gradient = tape.gradient(cost, flattened_parameters)
 
-print("JACOBIAN CALCULATION TIME:", time.time() - start_time)
-print("JACOBIAN SHAPE:", [g.numpy() for g in gradient])
+print("GRADIENT CALCULATION TIME:", time.time() - start_time)
+print("GRADIENT:", [g.numpy() for g in gradient])
 
-# tf.profiler.experimental.stop()
+if PROFILE:
+    tf.profiler.experimental.stop()