Finish CuTensorNet class for cuQuantum cutensornet
This commit is contained in:
@@ -1,21 +1,38 @@
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import numpy as np
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from qibo.backends.numpy import NumpyBackend
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from qibo.result import CircuitResult
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from qibo.config import raise_error
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class CuTensorNet(NumpyBackend): # pragma: no cover
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# CI does not test for GPU
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def __init__(self):
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def __init__(self, MPI_enabled=False, MPS_enabled=False, NCCL_enabled=False):
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super().__init__()
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import cuquantum # pylint: disable=import-error
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from cuquantum import cutensornet as cutn # pylint: disable=import-error
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self.name = "qibotn"
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self.cuquantum = cuquantum
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self.cutn = cutn
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self.platform = "cutensornet"
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self.versions["cuquantum"] = self.cuquantum.__version__
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self.supports_multigpu = True
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self.MPI_enabled = MPI_enabled
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self.MPS_enabled = MPS_enabled
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self.NCCL_enabled = NCCL_enabled
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self.handle = self.cutn.create()
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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 __del__(self):
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if hasattr(self, "cutn"):
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self.cutn.destroy(self.handle)
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@@ -37,3 +54,128 @@ class CuTensorNet(NumpyBackend): # pragma: no cover
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)
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else:
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raise TypeError("Type can be either complex64 or complex128")
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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.cutn
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cutn = qibotn.cutn
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MPI_enabled = self.MPI_enabled
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MPS_enabled = self.MPS_enabled
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NCCL_enabled = self.NCCL_enabled
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if (
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MPI_enabled == False
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and MPS_enabled == False
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and NCCL_enabled == False
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state = cutn.eval(circuit, self.dtype)
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if (
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MPI_enabled == False
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and MPS_enabled == True
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and NCCL_enabled == False
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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gate_algo = {
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"qr_method": False,
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"svd_method": {
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"partition": "UV",
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"abs_cutoff": 1e-12,
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},
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} # make this user input
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state = cutn.eval_mps(circuit, gate_algo, self.dtype)
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if (
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MPI_enabled == True
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and MPS_enabled == False
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and NCCL_enabled == False
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state, rank = cutn.eval_tn_MPI_2(circuit, self.dtype, 32)
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if rank > 0:
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state = np.array(0)
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if (
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MPI_enabled == False
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and MPS_enabled == False
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and NCCL_enabled == True
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state, rank = cutn.eval_tn_nccl(circuit, self.dtype, 32)
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if rank > 0:
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state = np.array(0)
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if (
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MPI_enabled == False
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and MPS_enabled == False
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and NCCL_enabled == False
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state = cutn.eval_expectation(circuit, self.dtype)
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if (
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MPI_enabled == True
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and MPS_enabled == False
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and NCCL_enabled == False
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state, rank = cutn.eval_tn_MPI_2_expectation(
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circuit, self.dtype, 32)
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if rank > 0:
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state = np.array(0)
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if (
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MPI_enabled == False
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and MPS_enabled == False
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and NCCL_enabled == True
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):
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if initial_state is not None:
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raise_error(NotImplementedError,
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"QiboTN cannot support initial state.")
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state, rank = cutn.eval_tn_nccl_expectation(
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circuit, self.dtype, 32)
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if rank > 0:
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state = np.array(0)
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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(
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self, circuit, state.flatten(), nshots)
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return circuit._final_state
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