Added missing had_transpiled=True to quantum_kernel (#247)

* Added missing had_transpiled=True * added missing reno file * add missing words * fix typo
qiskit-community · Oct 20, 2021 · 7f7bde7 · 7f7bde7
1 parent 9c7e313
commit 7f7bde7
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Showing 3 changed files with 11 additions and 2 deletions.
diff --git a/.pylintdict b/.pylintdict
@@ -167,6 +167,8 @@ traceback
 transpilation
 transpile
 transpiled
+transpiler
+transpiles
 uncompiled
 transpiling
 unitaries

diff --git a/qiskit_machine_learning/kernels/quantum_kernel.py b/qiskit_machine_learning/kernels/quantum_kernel.py
@@ -428,7 +428,7 @@ def evaluate(self, x_vec: np.ndarray, y_vec: np.ndarray = None) -> np.ndarray:
                     parameterized_circuit.assign_parameters({feature_map_params: x})
                     for x in to_be_computed_data[min_idx:max_idx]
                 ]
-                results = self._quantum_instance.execute(circuits)
+                results = self._quantum_instance.execute(circuits, had_transpiled=True)
                 for j in range(max_idx - min_idx):
                     statevectors.append(results.get_statevector(j))
 
@@ -473,7 +473,7 @@ def evaluate(self, x_vec: np.ndarray, y_vec: np.ndarray = None) -> np.ndarray:
                     for x, y in to_be_computed_data_pair
                 ]
 
-                results = self._quantum_instance.execute(circuits)
+                results = self._quantum_instance.execute(circuits, had_transpiled=True)
 
                 matrix_elements = [
                     self._compute_overlap(circuit, results, is_statevector_sim, measurement_basis)

diff --git a/releasenotes/notes/qsvm-transpiler-fix-13ab6b22a837d2b5.yaml b/releasenotes/notes/qsvm-transpiler-fix-13ab6b22a837d2b5.yaml
@@ -0,0 +1,7 @@
+---
+features:
+  - |
+    ``QuantumKernel`` transpiles all circuits before execution. However, this
+     information was not being passed, which calls the transpiler many times
+     during the execution of the ``QSVC/QSVR`` algorithm. Now, ``had_transpiled=True``
+     is passed correctly and the algorithm runs faster.