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Raise warning when falling back on param-shift #224

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Jan 18, 2024
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Raise warning when falling back on param-shift #224

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9 changes: 9 additions & 0 deletions src/braket/pennylane_plugin/braket_device.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@

import collections
import numbers
import warnings
from collections.abc import Iterable, Sequence

# pylint: disable=invalid-name
Expand Down Expand Up @@ -848,6 +849,14 @@ def execute_and_gradients(self, circuits, **kwargs):
new_jac = np.tensor([])
elif len(observables) != 1 or measurements[0].return_type != Expectation:
gradient_circuits, post_processing_fn = param_shift(circuit)
warnings.warn(
"This circuit cannot be differentiated with the adjoint method. "
"Falling back to the parameter-shift method, which will execute "
f"{len(gradient_circuits)} circuits. "
"To use the adjoint gradient method, make sure the circuit's only measurement "
"is an expectation of one observable. "
"To avoid gradient calculation, mark parameters with `requires_grad=False`."
)
grad_circuit_results = [
self.execute(c, compute_gradient=False) for c in gradient_circuits
]
Expand Down