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[pre-commit.ci] auto fixes from pre-commit.com hooks

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pre-commit-ci[bot]
2025-01-27 11:29:47 +00:00
parent 43ebd79cec
commit 80bfc7e876
5 changed files with 56 additions and 57 deletions
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6
src/qibotn/backends/__init__.py
View File

@@ -2,10 +2,10 @@ from typing import Union
from qibo.config import raise_error
from qibotn.backends.cutensornet import CuTensorNet # pylint: disable=E0401
from qibotn.backends.quimb import QuimbBackend # pylint: disable=E0401
from qibotn.backends.qmatchatea import QMatchaTeaBackend # pylint: disable=E0401
from qibotn.backends.abstract import QibotnBackend
from qibotn.backends.cutensornet import CuTensorNet # pylint: disable=E0401
from qibotn.backends.qmatchatea import QMatchaTeaBackend # pylint: disable=E0401
from qibotn.backends.quimb import QuimbBackend # pylint: disable=E0401
QibotnBackend = Union[CuTensorNet, QuimbBackend, QMatchaTeaBackend]

13
src/qibotn/backends/abstract.py
View File

@@ -1,11 +1,11 @@
from abc import abstractmethod
from qibo.backends.numpy import NumpyBackend
from qibo.config import raise_error
DEFAULT_CONFIGURATION = {
"MPI_enabled": False, # TODO: cutensornet specific, TBRemoved
"NCCL_enabled": False, # TODO: cutensornet specific, TBRemoved
"MPI_enabled": False, # TODO: cutensornet specific, TBRemoved
"NCCL_enabled": False, # TODO: cutensornet specific, TBRemoved
"expectation_enabled": False,
"pauli_string_pattern": None,
"MPS_enabled": False,
@@ -14,10 +14,9 @@ DEFAULT_CONFIGURATION = {
}
class QibotnBackend(NumpyBackend):
def __init__(self, runcard:dict = DEFAULT_CONFIGURATION):
def __init__(self, runcard: dict = DEFAULT_CONFIGURATION):
super().__init__()
def apply_gate(self, gate, state, nqubits): # pragma: no cover
@@ -32,10 +31,8 @@ class QibotnBackend(NumpyBackend):
def set_precision(self, precision):
if precision != self.precision:
super().set_precision(precision)
@abstractmethod
def configure_tn_simulation(self, **config):
"""Configure the TN simulation that will be performed."""
pass

1
src/qibotn/backends/cutensornet.py
View File

@@ -82,7 +82,6 @@ class CuTensorNet(QibotnBackend): # pragma: no cover
if hasattr(self, "cutn"):
self.cutn.destroy(self.handle)
def cuda_type(self, dtype="complex64"):
"""Get CUDA Type.

91
src/qibotn/backends/qmatchatea.py
View File

@@ -1,103 +1,108 @@
"""Implementation of Quantum Matcha Tea backend"""
"""Implementation of Quantum Matcha Tea backend."""
from dataclasses import dataclass
from qibo.config import raise_error
from qiskit import QuantumCircuit
from qibotn.backends.abstract import QibotnBackend
from qibo.config import raise_error
@dataclass
class QMatchaTeaBackend(QibotnBackend):
def __init__(self):
def __init__(self):
super().__init__()
import qiskit # pylint: disable=import-error
import qmatchatea # pylint: disable=import-error
import qiskit # pylint: disable=import-error
import qtealeaves # pylint: disable=import-error
import qtealeaves # pylint: disable=import-error
self.qmatchatea = qmatchatea
self.qiskit = qiskit
self.qtleaves = qtealeaves
# Set default configurations
self.configure_tn_simulation()
# TODO: update this function whenever ``set_device`` and ``set_precision``
# are set (?)
self._setup_qmatchatea_backend()
def execute_circuit(
self, circuit, initial_state=None, nshots=None, return_array=False
self, circuit, initial_state=None, nshots=None, return_array=False
):
# TODO: verify if the QCIO mechanism of matcha is supported by Fortran only
# as written in the docstrings or by Python too (see ``io_info`` argument of
# as written in the docstrings or by Python too (see ``io_info`` argument of
# ``qmatchatea.interface.run_simulation`` function)
if initial_state is not None:
raise_error(
NotImplementedError,
f"Backend {self.name}-{self.platform} currently does not support initial state."
f"Backend {self.name}-{self.platform} currently does not support initial state.",
)
# TODO: do we want to keep it like this or we aim to implement a different
# idea of "shots" here?
# TODO: do we want to keep it like this or we aim to implement a different
# idea of "shots" here?
nshots = None
circuit = self._qibocirc_to_qiskitcirc(circuit)
run_qk_params = self.qmatchatea.preprocessing.qk_transpilation_params(False)
results = self.qmatchatea.run_simulation(
circ = circuit,
convergence_parameters = self.convergence_params,
transpilation_parameters = run_qk_params,
backend = self.qmatchatea_backend,
circ=circuit,
convergence_parameters=self.convergence_params,
transpilation_parameters=run_qk_params,
backend=self.qmatchatea_backend,
)
# TODO: construct a proper TNResult object?
# It does not make sense to reconstruct QuantumState here!
return results.measure_probabilities
def configure_tn_simulation(
self,
convergence_params = None,
ansatz: str = "MPS",
):
"""
Configure TN simulation given Quantum Matcha Tea interface.
self,
convergence_params=None,
ansatz: str = "MPS",
):
"""Configure TN simulation given Quantum Matcha Tea interface.
Args:
ansatz (str): tensor network ansatz. It can be tree tensor network "TTN"
or Matrix Product States "MPS" (default).
convergence_params (qmatchatea.utils.QCConvergenceParameters):
convergence parameters class adapted to the quantum computing
convergence_params (qmatchatea.utils.QCConvergenceParameters):
convergence parameters class adapted to the quantum computing
execution. See https://baltig.infn.it/quantum_matcha_tea/py_api_quantum_matcha_tea/-/blob/master/qmatchatea/utils/utils.py?ref_type=heads#L540
for more instructions. If not passed, the default values proposed
for more instructions. If not passed, the default values proposed
by Quantum Matcha Tea's authors are set.
"""
# Set configurationsor defaults
self.convergence_params = convergence_params or self.qmatchatea.QCConvergenceParameters()
self.convergence_params = (
convergence_params or self.qmatchatea.QCConvergenceParameters()
)
self.ansatz = ansatz
# Initializing the TNObservables according to qmatchatea
# Initializing the TNObservables according to qmatchatea
self.observables = self.qtleaves.observables.TNObservables()
def _setup_qmatchatea_backend(self):
"""Configure qmatchatea QCBackend object."""
self.qmatchatea_device = "cpu" if "CPU" in self.device else "gpu" if "GPU" in self.device else None
self.qmatchatea_precision = "C" if self.precision == "single" else "Z" if self.precision == "double" else "A"
self.qmatchatea_device = (
"cpu" if "CPU" in self.device else "gpu" if "GPU" in self.device else None
)
self.qmatchatea_precision = (
"C"
if self.precision == "single"
else "Z" if self.precision == "double" else "A"
)
# TODO: once MPI is available for Python, integrate it here
self.qmatchatea_backend = self.qmatchatea.QCBackend(
backend = "PY", # The only alternative is Fortran, but we use Python here
precision = self.qmatchatea_precision,
device = self.qmatchatea_device,
ansatz = self.ansatz,
backend="PY", # The only alternative is Fortran, but we use Python here
precision=self.qmatchatea_precision,
device=self.qmatchatea_device,
ansatz=self.ansatz,
)
def _qibocirc_to_qiskitcirc(self, qibo_circuit) -> QuantumCircuit:
@@ -106,11 +111,11 @@ class QMatchaTeaBackend(QibotnBackend):
qasm_circuit = qibo_circuit.to_qasm()
qiskit_circuit = QuantumCircuit.from_qasm_str(qasm_circuit)
# Transpile the circuit to adapt it to the linear structure of the MPS,
# Transpile the circuit to adapt it to the linear structure of the MPS,
# with the constraint of having only the gates basis_gates
qiskit_circuit = self.qmatchatea.preprocessing.preprocess(
qiskit_circuit,
qk_params=self.qmatchatea.preprocessing.qk_transpilation_params()
qiskit_circuit,
qk_params=self.qmatchatea.preprocessing.qk_transpilation_params(),
)
return qiskit_circuit
return qiskit_circuit

2
src/qibotn/backends/quimb.py
View File

@@ -1,4 +1,3 @@
from qibo.backends.numpy import NumpyBackend
from qibo.config import raise_error
from qibo.result import QuantumState
@@ -38,7 +37,6 @@ class QuimbBackend(QibotnBackend):
self.platform = "QuimbBackend"
self.versions["quimb"] = self.quimb.__version__
def execute_circuit(
self, circuit, initial_state=None, nshots=None, return_array=False
): # pragma: no cover