Skip to main content

JIT compiles and executes programs written in QIR (Quantum Intermediate Representation).

Project description

QIR Runner

This project implements a basic QIR runtime and execution tool. Once installed, qir-runner will be available via the command line in your python environment as well as the qirrunner module which can be imported into a Python program.

Usage

Command line

Usage: qir-runner [OPTIONS] --file <PATH>

Options:
  -f, --file <PATH>        (Required) Path to the QIR file to run
  -e, --entrypoint <NAME>  Name of the entry point function to execute
  -s, --shots <NUM>        The number of times to repeat the execution of the chosen entry point in the program [default: 1]
  -r, --rngseed <NUM>      The value to use when seeding the random number generator used for quantum simulation
  -h, --help               Print help
  -V, --version            Print version

Python module

From a Python program, qirrunner provides a run function and two output helpers Output and OutputHandler. If the output_fn parameter of run is not specified, output will be written to stdout. Supplying the parameter allows the output of the execution to be captured.

from qirrunner import run, OutputHandler

path = "./runner/tests/resources/bv.bc"

handler = OutputHandler()
run(path, shots=2, output_fn=handler.handle)

print(handler.get_output())

Installation

pip install qirrunner

Installing from sdist

Platforms for which qirrunner doesn't have pre-built wheels (such as aarch64 macos), installation is available via sdist. Before installing qirrunner via pip:

  • Install a usable LLVM distribution which has llvm-config available.
  • Set the LLVM_SYS_140_PREFIX environment variable to the LLVM installation directory
    • example: export LLVM_SYS_140_PREFIX=/Users/sample/llvm
  • Install: python -m pip install qirrunner
    • This will build qirrunner from source. You will need a working Rust installation in order for this to compile.

Implemented APIs

double @__quantum__qis__arccos__body(double)
double @__quantum__qis__arcsin__body(double)
double @__quantum__qis__arctan__body(double)
double @__quantum__qis__arctan2__body(double)
void @__quantum__qis__assertmeasurementprobability__body(%Array*, %Array*, %Result*, double, %String*, double)
void @__quantum__qis__assertmeasurementprobability__ctl(%Array*, %Tuple*)
void @__quantum__qis__ccx__body(%Qubit*, %Qubit*)
void @__quantum__qis__cnot__body(%Qubit*, %Qubit*)
double @__quantum__qis__cos__body(double)
double @__quantum__qis__cosh__body(double)
void @__quantum__qis__cx__body(%Qubit*, %Qubit*)
void @__quantum__qis__cy__body(%Qubit*, %Qubit*)
void @__quantum__qis__cz__body(%Qubit*, %Qubit*)
double @__quantum__qis__drawrandomdouble__body()
i64 @__quantum__qis__drawrandomint__body()
void @__quantum__qis__dumpmachine__body()
void @__quantum__qis__exp__adj(%Array*, double, %Array*)
void @__quantum__qis__exp__body(%Array*, double, %Array*)
void @__quantum__qis__exp__ctl(%Array*, %Tuple*)
void @__quantum__qis__exp__ctladj(%Array*, %Tuple*)
void @__quantum__qis__exp__ctl(%Array*, %Tuple*)
void @__quantum__qis__h__body(%Qubit*)
void @__quantum__qis__h__ctl(%Array*, %Qubit*)
double @__quantum__qis__ieeeremainder__body(double, double)
double @__quantum__qis__infinity__body()
i1 @__quantum__qis__isinf__body()
i1 @__quantum__qis__isnan__body()
i1 @__quantum__qis__isnegativeinfinity__body()
double @__quantum__qis__log__body(double)
%Result* @__quantum__qis__m__body(%Qubit*)
%Result* @__quantum__qis__measure__body(%Array*, %Array*)
%Result* @__quantum__qis__mresetz__body(%Qubit*)
void @__quantum__qis__mz__body(%Qubit*, %Result*)
double @__quantum__qis__nan__body()
void @__quantum__qis__r__adj(i2, double, %Qubit*)
void @__quantum__qis__r__body(i2, double, %Qubit*)
void @__quantum__qis__r__ctl(%Array*, %Tuple*)
void @__quantum__qis__r__ctladj(%Array*, %Tuple*)
bool @__quantum__qis__read_result__body(%Result*)
void @__quantum__qis__reset__body(%Qubit*)
void @__quantum__qis__rx__body(double, %Qubit*)
void @__quantum__qis__rx__ctl(%Array*, %Tuple*)
void @__quantum__qis__rxx__body(double, %Qubit*, %Qubit*)
void @__quantum__qis__ry__body(double, %Qubit*)
void @__quantum__qis__ry__ctl(%Array*, %Tuple*)
void @__quantum__qis__ryy__body(double, %Qubit*, %Qubit*)
void @__quantum__qis__rz__body(double, %Qubit*)
void @__quantum__qis__rz__ctl(%Array*, %Tuple*)
void @__quantum__qis__rzz__body(double, %Qubit*, %Qubit*)
void @__quantum__qis__s__adj(%Qubit*)
void @__quantum__qis__s__body(%Qubit*)
void @__quantum__qis__s__ctl(%Array*, %Qubit*)
void @__quantum__qis__s__ctladj(%Array*, %Qubit*)
double @__quantum__qis__sin__body(double)
double @__quantum__qis__sinh__body(double)
double @__quantum__qis__sqrt__body(double)
void @__quantum__qis__swap__body(%Qubit*, %Qubit*)
void @__quantum__qis__t__adj(%Qubit*)
void @__quantum__qis__t__body(%Qubit*)
void @__quantum__qis__t__ctl(%Array*, %Qubit*)
void @__quantum__qis__t__ctladj(%Array*, %Qubit*)
double @__quantum__qis__tan__body(double)
double @__quantum__qis__tanh__body(double)
void @__quantum__qis__x__body(%Qubit*)
void @__quantum__qis__x__ctl(%Array*, %Qubit*)
void @__quantum__qis__y__body(%Qubit*)
void @__quantum__qis__y__ctl(%Array*, %Qubit*)
void @__quantum__qis__z__body(%Qubit*)
void @__quantum__qis__z__ctl(%Array*, %Qubit*)
%Array* @__quantum__rt__array_concatenate(%Array*, %Array*)
%Array* @__quantum__rt__array_copy(%Array*, bool)
%Array* @__quantum__rt__array_create_1d(i32, i64)
i8* @__quantum__rt__array_get_element_ptr_1d(%Array*, i64)
i64 @__quantum__rt__array_get_size_1d(%Array*)
void @__quantum__rt__array_record_output(i64, i8*)
void @__quantum__rt__array_update_alias_count(%Array*, i32)
void @__quantum__rt__array_update_reference_count(%Array*, i32)
%BigInt* @__quantum__rt__bigint_add(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_bitand(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_bitnot(%BigInt*)
%BigInt* @__quantum__rt__bigint_bitor(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_bitxor(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_create_array(i32, i8*)
%BigInt* @__quantum__rt__bigint_create_i64(i64)
%BigInt* @__quantum__rt__bigint_divide(%BigInt*, %BigInt*)
bool @__quantum__rt__bigint_equal(%BigInt*, %BigInt*)
i8* @__quantum__rt__bigint_get_data(%BigInt*)
i32 @__quantum__rt__bigint_get_length(%BigInt*)
bool @__quantum__rt__bigint_greater(%BigInt*, %BigInt*)
bool @__quantum__rt__bigint_greater_eq(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_modulus(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_multiply(%BigInt*, %BigInt*)
%BigInt* @__quantum__rt__bigint_negate(%BigInt*)
%BigInt* @__quantum__rt__bigint_power(%BigInt*, i32)
%BigInt* @__quantum__rt__bigint_shiftleft(%BigInt*, i64)
%BigInt*@__quantum__rt__bigint_shiftright(%BigInt*, i64)
void @__quantum__rt__bigint_subtract(%BigInt*, %BigInt*)
%String* @__quantum__rt__bigint_to_string(%BigInt*)
void @__quantum__rt__bigint_update_reference_count(%BigInt*, i32)
void @__quantum__rt__bool_record_output(i1, i8*)
%String* @__quantum__rt__bool_to_string(i1)
%Callable* @__quantum__rt__callable_copy(%Callable*, bool)
%Callable* @__quantum__rt__callable_create([4 x void(%Tuple*, %Tuple*, %Tuple*)*]*, [2 x void (%Tuple*, i32)]*, %Tuple*)
void @__quantum__rt__callable_invoke(%Callable*, %Tuple*, %Tuple*)
void @__quantum__rt__callable_make_adjoint(%Callable*)
void @__quantum__rt__callable_make_controlled(%Callable*)
void @__quantum__rt__callable_update_alias_count(%Callable*, i32)
void @__quantum__rt__callable_update_reference_count(%Callable*, i32)
void @__quantum__rt__capture_update_alias_count(%Callable*, i32)
void @__quantum__rt__capture_update_reference_count(%Callable*, i32)
void @__quantum__rt__double_record_output(double, i8*)
%String* @__quantum__rt__double_to_string(double)
void @__quantum__rt__fail(%String*)
void @__quantum__rt__int_record_output(i64, i8*)
%String* @__quantum__rt__int_to_string(i64)
i8* @__quantum__rt__memory_allocate(i64)
void @__quantum__rt__message(%String*)
void @__quantum__rt__message_record_output(%String*)
%String* @__quantum__rt__pauli_to_string(i2)
%Qubit* @__quantum__rt__qubit_allocate()
%Array* @__quantum__rt__qubit_allocate_array(i64)
void @__quantum__rt__qubit_release(%Qubit*)
void @__quantum__rt__qubit_release_array(%Array*)
%String* @__quantum__rt__qubit_to_string(%Qubit*)
bool @__quantum__rt__result_equal(%Result*, %Result*)
%Result* @__quantum__rt__result_get_one()
%Result* @__quantum__rt__result_get_zero()
void @__quantum__rt__result_record_output(%Result*, i8*)
%String* @__quantum__rt__result_to_string(%Result*)
void @__quantum__rt__result_update_reference_count(%Result*, i32)
%String* @__quantum__rt__string_concatenate(%String*, %String*)
%String* @__quantum__rt__string_create(i8*)
bool @__quantum__rt__string_equal(%String*, %String*)
i8* @__quantum__rt__string_get_data(%String*)
i32 @__quantum__rt__string_get_length(%String*)
void @__quantum__rt__string_update_reference_count(%String*, i32)
%Tuple* @__quantum__rt__tuple_copy(%Tuple*, i1)
%Tuple* @__quantum__rt__tuple_create(i64)
void @__quantum__rt__tuple_record_output(i64, i8*)
void @__quantum__rt__tuple_update_alias_count(%Tuple*, i32)
void @__quantum__rt__tuple_update_reference_count(%Tuple*, i32)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qirrunner-0.7.6.tar.gz (256.1 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

qirrunner-0.7.6-cp38-abi3-win_amd64.whl (14.0 MB view details)

Uploaded CPython 3.8+Windows x86-64

qirrunner-0.7.6-cp38-abi3-manylinux_2_34_x86_64.manylinux_2_35_x86_64.whl (24.5 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.34+ x86-64manylinux: glibc 2.35+ x86-64

qirrunner-0.7.6-cp38-abi3-manylinux_2_34_aarch64.manylinux_2_35_aarch64.whl (22.7 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.34+ ARM64manylinux: glibc 2.35+ ARM64

qirrunner-0.7.6-cp38-abi3-macosx_10_12_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.8+macOS 10.12+ x86-64

File details

Details for the file qirrunner-0.7.6.tar.gz.

File metadata

  • Download URL: qirrunner-0.7.6.tar.gz
  • Upload date:
  • Size: 256.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: RestSharp/106.13.0.0

File hashes

Hashes for qirrunner-0.7.6.tar.gz
Algorithm Hash digest
SHA256 af09e40e8c246f31b8226eebd84a8b3f18d7d603c33243826b13dd5f9adf53c7
MD5 0326275c686362e4a7b2f93ff9c7c298
BLAKE2b-256 873b0fad0ecec7ff496ecacf40caf98c54f0e5b17cc3238507eed03caf6e1b78

See more details on using hashes here.

File details

Details for the file qirrunner-0.7.6-cp38-abi3-win_amd64.whl.

File metadata

  • Download URL: qirrunner-0.7.6-cp38-abi3-win_amd64.whl
  • Upload date:
  • Size: 14.0 MB
  • Tags: CPython 3.8+, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: RestSharp/106.13.0.0

File hashes

Hashes for qirrunner-0.7.6-cp38-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 e8b2e4297f9a239c15fbe6b8ae091dd6c51820d85661d0d74cea5bd95ae6d644
MD5 04d6b21698c2a4fa6673b705bdde63a6
BLAKE2b-256 4a5977eaec2ca63c764eb65ac854635e581277937fd401be2de5dbc5b9daabf7

See more details on using hashes here.

File details

Details for the file qirrunner-0.7.6-cp38-abi3-manylinux_2_34_x86_64.manylinux_2_35_x86_64.whl.

File metadata

File hashes

Hashes for qirrunner-0.7.6-cp38-abi3-manylinux_2_34_x86_64.manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 a8c8d679199ab9e9ce0a8c8460cd82ac42c322dd73df06c48c1235b069dc91b7
MD5 06e8544ab61f6af0aac0c473cdb22ad9
BLAKE2b-256 1fe65b91045f0ee6ef319fc0b1d7d8795635126e5059908f27986c131bf44f9c

See more details on using hashes here.

File details

Details for the file qirrunner-0.7.6-cp38-abi3-manylinux_2_34_aarch64.manylinux_2_35_aarch64.whl.

File metadata

File hashes

Hashes for qirrunner-0.7.6-cp38-abi3-manylinux_2_34_aarch64.manylinux_2_35_aarch64.whl
Algorithm Hash digest
SHA256 9cb8681aae618495c6fddcc601079485f01463374b44b6b64b26c1717552165b
MD5 fa61fe7963226b2f29a7d49fdc959b06
BLAKE2b-256 d53b7db92908dc690dc1a41b022539e6fa8848a59b92b3a0eb146dca26d0cc22

See more details on using hashes here.

File details

Details for the file qirrunner-0.7.6-cp38-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for qirrunner-0.7.6-cp38-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 7516a707a7290819c8a126731b8e1ed555c290bb5351f5a75c37ab56769a7495
MD5 21f6172cc99336d924b7ad52a7b5b31c
BLAKE2b-256 fab7cd2023d26eff1c95466b56d73230a33be2a5ebc622b802f1c5e27db727b2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page