Merge branch 'master' into custom_lattice_function

PennyLaneAI · Sep 20, 2024 · ac7e49f · ac7e49f
2 parents 4b39e33 + 6d98c51
commit ac7e49f
Show file tree

Hide file tree

Showing 4 changed files with 19 additions and 18 deletions.
diff --git a/doc/development/release_notes.md b/doc/development/release_notes.md
@@ -5,8 +5,6 @@ This page contains the release notes for PennyLane.
 
 .. mdinclude:: ../releases/changelog-dev.md
 
-.. mdinclude:: ../releases/changelog-0.38.1.md
-
 .. mdinclude:: ../releases/changelog-0.38.0.md
 
 .. mdinclude:: ../releases/changelog-0.37.0.md

diff --git a/doc/releases/changelog-0.38.1.md b/doc/releases/changelog-0.38.1.md
diff --git a/doc/releases/changelog-dev.md b/doc/releases/changelog-dev.md
@@ -166,6 +166,10 @@
 
 <h3>Bug fixes 🐛</h3>
 
+* Fix float-to-complex casting in various places across PennyLane.
+ [(#6260)](https://github.com/PennyLaneAI/pennylane/pull/6260)
+ [(#6268)](https://github.com/PennyLaneAI/pennylane/pull/6268)
+
 * Fix a bug where zero-valued JVPs were calculated wrongly in the presence of shot vectors.
   [(#6219)](https://github.com/PennyLaneAI/pennylane/pull/6219)
 

diff --git a/pennylane/devices/qubit/apply_operation.py b/pennylane/devices/qubit/apply_operation.py
@@ -71,7 +71,13 @@ def apply_operation_einsum(op: qml.operation.Operator, state, is_state_batched:
     Returns:
         array[complex]: output_state
     """
-    mat = qml.math.cast_like(op.matrix(), 1j)
+    # We use this implicit casting strategy as autograd raises ComplexWarnings
+    # when backpropagating if casting explicitly. Some type of casting is needed
+    # to prevent ComplexWarnings with backpropagation with other interfaces
+    if qml.math.get_interface(state) == "tensorflow":
+        mat = qml.math.cast_like(op.matrix(), state)
+    else:
+        mat = op.matrix() + 0j
 
     total_indices = len(state.shape) - is_state_batched
     num_indices = len(op.wires)
@@ -114,7 +120,14 @@ def apply_operation_tensordot(op: qml.operation.Operator, state, is_state_batche
     Returns:
         array[complex]: output_state
     """
-    mat = qml.math.cast_like(op.matrix(), 1j)
+    # We use this implicit casting strategy as autograd raises ComplexWarnings
+    # when backpropagating if casting explicitly. Some type of casting is needed
+    # to prevent ComplexWarnings with backpropagation with other interfaces
+    if qml.math.get_interface(state) == "tensorflow":
+        mat = qml.math.cast_like(op.matrix(), state)
+    else:
+        mat = op.matrix() + 0j
+
     total_indices = len(state.shape) - is_state_batched
     num_indices = len(op.wires)