mirror of https://github.com/Qiskit/qiskit-aer.git
124 lines
3.9 KiB
Python
124 lines
3.9 KiB
Python
# This code is part of Qiskit.
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#
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# (C) Copyright IBM 2018, 2021.
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#
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# This code is licensed under the Apache License, Version 2.0. You may
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# obtain a copy of this license in the LICENSE.txt file in the root directory
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# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
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#
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# Any modifications or derivative works of this code must retain this
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# copyright notice, and modified files need to carry a notice indicating
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# that they have been altered from the originals.
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"""
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Integration Tests for SaveState instruction
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"""
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import numpy as np
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from ddt import ddt
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from test.terra.backends.simulator_test_case import SimulatorTestCase, supported_methods
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from qiskit import QuantumCircuit, transpile
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from qiskit_aer.library import (
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SaveStatevector,
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SaveDensityMatrix,
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SaveStabilizer,
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SaveMatrixProductState,
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SaveUnitary,
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SaveSuperOp,
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)
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@ddt
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class TestSaveState(SimulatorTestCase):
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"""Test instructions for saving simulator state."""
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@supported_methods(
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[
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"automatic",
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"statevector",
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"density_matrix",
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"stabilizer",
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"matrix_product_state",
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"unitary",
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"superop",
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"tensor_network",
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]
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)
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def test_save_state(self, method, device):
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"""Test save_amplitudes instruction"""
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REFERENCE_SAVE = {
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"automatic": SaveStabilizer,
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"stabilizer": SaveStabilizer,
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"statevector": SaveStatevector,
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"density_matrix": SaveDensityMatrix,
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"matrix_product_state": SaveMatrixProductState,
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"unitary": SaveUnitary,
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"superop": SaveSuperOp,
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"tensor_network": SaveStatevector,
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}
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backend = self.backend(method=method, device=device)
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if method == "automatic":
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label = "stabilizer"
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else:
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label = method
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# Stabilizer test circuit
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num_qubits = 2
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target_instr = REFERENCE_SAVE[method](num_qubits, label="target")
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circ = QuantumCircuit(num_qubits)
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circ.h(0)
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for i in range(1, num_qubits):
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circ.cx(i - 1, i)
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circ.save_state()
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circ.append(target_instr, range(num_qubits))
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# Run
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result = backend.run(transpile(circ, backend, optimization_level=0), shots=1).result()
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self.assertTrue(result.success)
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simdata = result.data(0)
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self.assertIn(label, simdata)
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self.assertIn("target", simdata)
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value = simdata[label]
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target = simdata["target"]
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if method == "matrix_product_state":
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for val, targ in zip(value[0], target[0]):
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self.assertTrue(np.allclose(val, targ))
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for val, targ in zip(value[1], target[1]):
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self.assertTrue(np.allclose(val, targ))
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else:
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self.assertEqual(value, target)
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@supported_methods(["statevector", "density_matrix"])
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def test_save_state_cache_blocking(self, method, device):
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"""Test save_amplitudes instruction"""
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REFERENCE_SAVE = {
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"statevector": SaveStatevector,
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"density_matrix": SaveDensityMatrix,
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}
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backend = self.backend(
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method=method, device=device, blocking_qubits=2, max_parallel_threads=1
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)
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# Stabilizer test circuit
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num_qubits = 4
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target_instr = REFERENCE_SAVE[method](num_qubits, label="target")
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circ = QuantumCircuit(num_qubits)
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circ.h(0)
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for i in range(1, num_qubits):
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circ.cx(i - 1, i)
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circ.save_state()
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circ.append(target_instr, range(num_qubits))
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# Run
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result = backend.run(transpile(circ, backend, optimization_level=0), shots=1).result()
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self.assertTrue(result.success)
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simdata = result.data(0)
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self.assertIn(method, simdata)
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self.assertIn("target", simdata)
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value = simdata[method]
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target = simdata["target"]
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self.assertEqual(value, target)
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