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Update casting for apply_operation #6268

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merged 6 commits into from
Sep 20, 2024
Merged

Update casting for apply_operation #6268

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74ce1d7
Update casting for applying matrices to sv
mudit2812 Sep 13, 2024
8346c6b
Update pytest.ini
mudit2812 Sep 16, 2024
f0096c7
Merge branch 'master' into implicit-casting
mudit2812 Sep 20, 2024
0d2bf9b
Update changelog
mudit2812 Sep 20, 2024
d557709
Add conditional casting for tf
mudit2812 Sep 20, 2024
6ccb3fb
Merge branch 'master' into implicit-casting
mudit2812 Sep 20, 2024
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2 changes: 0 additions & 2 deletions doc/development/release_notes.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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
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14 changes: 0 additions & 14 deletions doc/releases/changelog-0.38.1.md
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4 changes: 4 additions & 0 deletions doc/releases/changelog-dev.md
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Expand Up @@ -163,6 +163,10 @@

<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)
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* Fix a bug where zero-valued JVPs were calculated wrongly in the presence of shot vectors.
[(#6219)](https://github.com/PennyLaneAI/pennylane/pull/6219)

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17 changes: 15 additions & 2 deletions pennylane/devices/qubit/apply_operation.py
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Expand Up @@ -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)
Expand Down Expand Up @@ -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)

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