Source code for pyquil.api._abstract_compiler

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# Copyright 2018 Rigetti Computing
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#    Licensed under the Apache License, Version 2.0 (the "License");
#    you may not use this file except in compliance with the License.
#    You may obtain a copy of the License at
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#        http://www.apache.org/licenses/LICENSE-2.0
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#    Unless required by applicable law or agreed to in writing, software
#    distributed under the License is distributed on an "AS IS" BASIS,
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from abc import ABC, abstractmethod
from dataclasses import dataclass
import dataclasses
from typing import Any, Dict, List, Optional, Sequence, Union

from pyquil._memory import Memory
from pyquil._version import pyquil_version
from pyquil.api._compiler_client import CompilerClient, CompileToNativeQuilRequest
from pyquil.external.rpcq import compiler_isa_to_target_quantum_processor
from pyquil.parser import parse_program
from pyquil.paulis import PauliTerm
from pyquil.quantum_processor import AbstractQuantumProcessor
from pyquil.quil import Program
from pyquil.quilatom import ExpressionDesignator, MemoryReference
from pyquil.quilbase import Gate
from qcs_api_client.client import QCSClientConfiguration
from rpcq.messages import NativeQuilMetadata, ParameterAref, ParameterSpec


class QuilcVersionMismatch(Exception):
    pass


class QuilcNotRunning(Exception):
    pass


[docs]@dataclass class EncryptedProgram: """ Encrypted binary, executable on a QPU. """ program: str """String representation of an encrypted Quil program.""" memory_descriptors: Dict[str, ParameterSpec] """Descriptors for memory executable's regions, mapped by name.""" ro_sources: Dict[MemoryReference, str] """Readout sources, mapped by memory reference.""" recalculation_table: Dict[ParameterAref, ExpressionDesignator] """A mapping from memory references to the original gate arithmetic.""" _memory: Memory """Memory values (parameters) to be sent with the program."""
[docs] def copy(self) -> "EncryptedProgram": """ Return a deep copy of this EncryptedProgram. """ return dataclasses.replace(self, _memory=self._memory.copy())
[docs] def write_memory( self, *, region_name: str, value: Union[int, float, Sequence[int], Sequence[float]], offset: Optional[int] = None, ) -> "EncryptedProgram": self._memory._write_value(parameter=ParameterAref(name=region_name, index=(offset or 0)), value=value) return self
QuantumExecutable = Union[EncryptedProgram, Program]
[docs]class AbstractCompiler(ABC): """The abstract interface for a compiler.""" def __init__( self, *, quantum_processor: AbstractQuantumProcessor, timeout: float, client_configuration: Optional[QCSClientConfiguration], ) -> None: self.quantum_processor = quantum_processor self._timeout = timeout self._client_configuration = client_configuration or QCSClientConfiguration.load() self._compiler_client = CompilerClient(client_configuration=self._client_configuration, request_timeout=timeout)
[docs] def get_version_info(self) -> Dict[str, Any]: """ Return version information for this compiler and its dependencies. :return: Dictionary of version information. """ return {"quilc": self._compiler_client.get_version()}
[docs] def quil_to_native_quil(self, program: Program, *, protoquil: Optional[bool] = None) -> Program: """ Compile an arbitrary quil program according to the ISA of ``self.quantum_processor``. :param program: Arbitrary quil to compile :param protoquil: Whether to restrict to protoquil (``None`` means defer to server) :return: Native quil and compiler metadata """ self._connect() compiler_isa = self.quantum_processor.to_compiler_isa() request = CompileToNativeQuilRequest( program=program.out(calibrations=False), target_quantum_processor=compiler_isa_to_target_quantum_processor(compiler_isa), protoquil=protoquil, ) response = self._compiler_client.compile_to_native_quil(request) nq_program = parse_program(response.native_program) nq_program.native_quil_metadata = ( None if response.metadata is None else NativeQuilMetadata( final_rewiring=response.metadata.final_rewiring, gate_depth=response.metadata.gate_depth, gate_volume=response.metadata.gate_volume, multiqubit_gate_depth=response.metadata.multiqubit_gate_depth, program_duration=response.metadata.program_duration, program_fidelity=response.metadata.program_fidelity, topological_swaps=response.metadata.topological_swaps, qpu_runtime_estimation=response.metadata.qpu_runtime_estimation, ) ) nq_program.num_shots = program.num_shots nq_program._calibrations = program.calibrations nq_program._memory = program._memory.copy() return nq_program
def _connect(self) -> None: try: _check_quilc_version(self._compiler_client.get_version()) except TimeoutError: raise QuilcNotRunning( f"Request to quilc at {self._compiler_client.base_url} timed out. " "This could mean that quilc is not running, is not reachable, or is " "responding slowly. See the Troubleshooting Guide: " "{DOCS_URL}/troubleshooting.html" )
[docs] @abstractmethod def native_quil_to_executable(self, nq_program: Program) -> QuantumExecutable: """ Compile a native quil program to a binary executable. :param nq_program: Native quil to compile :return: An (opaque) binary executable """
[docs] def reset(self) -> None: """ Reset the state of the this compiler. """ pass
def _check_quilc_version(version: str) -> None: """ Verify that there is no mismatch between pyquil and quilc versions. :param version: quilc version. """ major, minor, _ = map(int, version.split(".")) if major == 1 and minor < 8: raise QuilcVersionMismatch( "Must use quilc >= 1.8.0 with pyquil >= 2.8.0, but you " f"have quilc {version} and pyquil {pyquil_version}" ) class AbstractBenchmarker(ABC): @abstractmethod def apply_clifford_to_pauli(self, clifford: Program, pauli_in: PauliTerm) -> PauliTerm: r""" Given a circuit that consists only of elements of the Clifford group, return its action on a PauliTerm. In particular, for Clifford C, and Pauli P, this returns the PauliTerm representing PCP^{\dagger}. :param clifford: A Program that consists only of Clifford operations. :param pauli_in: A PauliTerm to be acted on by clifford via conjugation. :return: A PauliTerm corresponding to pauli_in * clifford * pauli_in^{\dagger} """ @abstractmethod def generate_rb_sequence( self, depth: int, gateset: Sequence[Gate], seed: Optional[int] = None, interleaver: Optional[Program] = None, ) -> List[Program]: """ Construct a randomized benchmarking experiment on the given qubits, decomposing into gateset. If interleaver is not provided, the returned sequence will have the form C_1 C_2 ... C_(depth-1) C_inv , where each C is a Clifford element drawn from gateset, C_{< depth} are randomly selected, and C_inv is selected so that the entire sequence composes to the identity. If an interleaver G (which must be a Clifford, and which will be decomposed into the native gateset) is provided, then the sequence instead takes the form C_1 G C_2 G ... C_(depth-1) G C_inv . The JSON response is a list of lists of indices, or Nones. In the former case, they are the index of the gate in the gateset. :param int depth: The number of Clifford gates to include in the randomized benchmarking experiment. This is different than the number of gates in the resulting experiment. :param list gateset: A list of pyquil gates to decompose the Clifford elements into. These must generate the clifford group on the qubits of interest. e.g. for one qubit [RZ(np.pi/2), RX(np.pi/2)]. :param seed: A positive integer used to seed the PRNG. :param interleaver: A Program object that encodes a Clifford element. :return: A list of pyquil programs. Each pyquil program is a circuit that represents an element of the Clifford group. When these programs are composed, the resulting Program will be the randomized benchmarking experiment of the desired depth. e.g. if the return programs are called cliffords then `sum(cliffords, Program())` will give the randomized benchmarking experiment, which will compose to the identity program. """