148 lines
4.7 KiB
Python
148 lines
4.7 KiB
Python
import numpy as np
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from qibo.backends.numpy import NumpyBackend
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from qibo.states import CircuitResult
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from qibo.config import raise_error
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class QuTensorNet(NumpyBackend):
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def __init__(self, runcard):
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super().__init__()
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import quimb # pylint: disable=import-error
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if runcard is not None:
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self.MPI_enabled = runcard.get("MPI_enabled", False)
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self.NCCL_enabled = runcard.get("NCCL_enabled", False)
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self.expectation_enabled_value = runcard.get("expectation_enabled", False)
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mps_enabled_value = runcard.get("MPS_enabled")
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if mps_enabled_value is True:
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self.MPS_enabled = True
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elif mps_enabled_value is False:
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self.MPS_enabled = False
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else:
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raise TypeError("MPS_enabled has an unexpected type")
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else:
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self.MPI_enabled = False
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self.MPS_enabled = False
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self.NCCL_enabled = False
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self.expectation_enabled = False
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self.name = "qibotn"
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self.quimb = quimb
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self.platform = "qutensornet"
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self.versions["quimb"] = self.quimb.__version__
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def apply_gate(self, gate, state, nqubits): # pragma: no cover
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raise_error(NotImplementedError, "QiboTN cannot apply gates directly.")
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def apply_gate_density_matrix(self, gate, state, nqubits): # pragma: no cover
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raise_error(NotImplementedError, "QiboTN cannot apply gates directly.")
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def assign_measurements(self, measurement_map, circuit_result):
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raise_error(NotImplementedError, "Not implemented in QiboTN.")
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def set_precision(self, precision):
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if precision != self.precision:
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super().set_precision(precision)
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def execute_circuit(
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self, circuit, initial_state=None, nshots=None, return_array=False
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): # pragma: no cover
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"""Executes a quantum circuit.
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Args:
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circuit (:class:`qibo.models.circuit.Circuit`): Circuit to execute.
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initial_state (:class:`qibo.models.circuit.Circuit`): Circuit to prepare the initial state.
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If ``None`` the default ``|00...0>`` state is used.
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Returns:
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xxx.
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"""
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import qibotn.eval_qu as eval_qu
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if (
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self.MPI_enabled == False
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and self.MPS_enabled == False
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and self.NCCL_enabled == False
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and self.expectation_enabled == False
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):
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state = eval.dense_vector_tn_qu(
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circuit, init_state, is_mps=False, backend="numpy"
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)
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elif (
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self.MPI_enabled == False
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and self.MPS_enabled == True
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and self.NCCL_enabled == False
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and self.expectation_enabled == False
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):
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state = eval.dense_vector_tn_qu(
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circuit, init_state, is_mps=True, backend="numpy"
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)
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elif (
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self.MPI_enabled == True
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and self.MPS_enabled == False
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and self.NCCL_enabled == False
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and self.expectation_enabled == False
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):
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raise_error(NotImplementedError, "QiboTN quimb backend cannot support MPI.")
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elif (
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self.MPI_enabled == False
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and self.MPS_enabled == False
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and self.NCCL_enabled == True
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and self.expectation_enabled == False
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):
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raise_error(
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NotImplementedError, "QiboTN quimb backend cannot support NCCL."
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)
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elif (
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self.MPI_enabled == False
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and self.MPS_enabled == False
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and self.NCCL_enabled == False
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and self.expectation_enabled == True
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):
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raise_error(
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NotImplementedError, "QiboTN quimb backend cannot support expectation"
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)
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elif (
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self.MPI_enabled == True
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and self.MPS_enabled == False
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and self.NCCL_enabled == False
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and self.expectation_enabled == True
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):
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raise_error(
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NotImplementedError, "QiboTN quimb backend cannot support expectation"
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)
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elif (
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self.MPI_enabled == False
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and self.MPS_enabled == False
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and self.NCCL_enabled == True
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and self.expectation_enabled == True
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):
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raise_error(
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NotImplementedError, "QiboTN quimb backend cannot support expectation"
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)
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else:
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raise_error(NotImplementedError, "Compute type not supported.")
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if return_array:
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return state.flatten()
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else:
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circuit._final_state = CircuitResult(self, circuit, state.flatten(), nshots)
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return circuit._final_state
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