From 76f9206edb03b4f717d90cf246066198f689e26a Mon Sep 17 00:00:00 2001
From: Arnav Nagzirkar <113314200+arnavnagzirkar@users.noreply.github.com>
Date: Tue, 2 Jun 2026 22:46:55 -0700
Subject: [PATCH 1/2] test: cover random circuits with channels

---
 tensorflow_quantum/python/util_test.py | 45 ++++++++++++++++++++++++++
 1 file changed, 45 insertions(+)

diff --git a/tensorflow_quantum/python/util_test.py b/tensorflow_quantum/python/util_test.py
index d22c118a8..3a062f85c 100644
--- a/tensorflow_quantum/python/util_test.py
+++ b/tensorflow_quantum/python/util_test.py
@@ -139,6 +139,51 @@ def test_random_symbol_circuit_resolver_batch_shapes_and_types(
                     isinstance(value, float)
                     for value in resolver.param_dict.values()))
 
+    def test_random_circuit_resolver_batch_channels_present(self):
+        """Confirm channel ops appear in circuits when include_channels=True."""
+        qubits = cirq.GridQubit.rect(1, 3)
+        channel_types = tuple(type(c) for c in util.get_supported_channels())
+
+        circuits, _ = util.random_circuit_resolver_batch(qubits,
+                                                         batch_size=5,
+                                                         n_moments=20,
+                                                         include_channels=True)
+
+        def has_channel(circuit):
+            return any(
+                isinstance(op.gate, channel_types)
+                for moment in circuit
+                for op in moment.operations)
+
+        self.assertTrue(
+            any(has_channel(c) for c in circuits),
+            "Expected at least one channel operation across batch when "
+            "include_channels=True")
+        # Verify circuits containing channels are serializable.
+        self.assertIsNotNone(util.convert_to_tensor(circuits))
+
+    def test_random_symbol_circuit_resolver_batch_channels_present(self):
+        """Confirm channel ops appear in circuits when include_channels=True."""
+        qubits = cirq.GridQubit.rect(1, 3)
+        symbols = ['alpha', 'beta']
+        channel_types = tuple(type(c) for c in util.get_supported_channels())
+
+        circuits, _ = util.random_symbol_circuit_resolver_batch(
+            qubits, symbols, batch_size=5, n_moments=20, include_channels=True)
+
+        def has_channel(circuit):
+            return any(
+                isinstance(op.gate, channel_types)
+                for moment in circuit
+                for op in moment.operations)
+
+        self.assertTrue(
+            any(has_channel(c) for c in circuits),
+            "Expected at least one channel operation across batch when "
+            "include_channels=True")
+        # Verify circuits containing channels are serializable.
+        self.assertIsNotNone(util.convert_to_tensor(circuits))
+
     @parameterized.parameters(_items_to_tensorize())
     def test_convert_to_tensor(self, item):
         """Test that the convert_to_tensor function works correctly by manually

From 9b1f9a81691e452aeca2cad945b958c7c5862617 Mon Sep 17 00:00:00 2001
From: Arnav Nagzirkar <113314200+arnavnagzirkar@users.noreply.github.com>
Date: Tue, 2 Jun 2026 23:05:07 -0700
Subject: [PATCH 2/2] test: round-trip serialize channel circuits

Address review feedback: verify channel-containing circuits survive a full convert_to_tensor/from_tensor round-trip instead of only asserting non-null serialization.
---
 tensorflow_quantum/python/util_test.py | 22 ++++++++++++++++++----
 1 file changed, 18 insertions(+), 4 deletions(-)

diff --git a/tensorflow_quantum/python/util_test.py b/tensorflow_quantum/python/util_test.py
index 3a062f85c..d198be69e 100644
--- a/tensorflow_quantum/python/util_test.py
+++ b/tensorflow_quantum/python/util_test.py
@@ -159,8 +159,15 @@ def has_channel(circuit):
             any(has_channel(c) for c in circuits),
             "Expected at least one channel operation across batch when "
             "include_channels=True")
-        # Verify circuits containing channels are serializable.
-        self.assertIsNotNone(util.convert_to_tensor(circuits))
+        # Verify circuits containing channels are correctly serializable
+        # round-trip.
+        serialized = util.convert_to_tensor(circuits,
+                                            deterministic_proto_serialize=True)
+        deserialized = util.from_tensor(serialized)
+        self.assertAllEqual(
+            serialized,
+            util.convert_to_tensor(deserialized,
+                                   deterministic_proto_serialize=True))
 
     def test_random_symbol_circuit_resolver_batch_channels_present(self):
         """Confirm channel ops appear in circuits when include_channels=True."""
@@ -181,8 +188,15 @@ def has_channel(circuit):
             any(has_channel(c) for c in circuits),
             "Expected at least one channel operation across batch when "
             "include_channels=True")
-        # Verify circuits containing channels are serializable.
-        self.assertIsNotNone(util.convert_to_tensor(circuits))
+        # Verify circuits containing channels are correctly serializable
+        # round-trip.
+        serialized = util.convert_to_tensor(circuits,
+                                            deterministic_proto_serialize=True)
+        deserialized = util.from_tensor(serialized)
+        self.assertAllEqual(
+            serialized,
+            util.convert_to_tensor(deserialized,
+                                   deterministic_proto_serialize=True))
 
     @parameterized.parameters(_items_to_tensorize())
     def test_convert_to_tensor(self, item):