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qiskitserverless 0.16.3
Qiskit Serverless client
Installation
pip install qiskit_serverless
Documentation
Full docs can be found at https://qiskit.github.io/qiskit-serverless/
Usage
Step 1: write funtion in ./src/function.py
from qiskit_serverless import distribute_task, get, get_arguments, save_result
from qiskit import QuantumCircuit
from qiskit.circuit.random import random_circuit
from qiskit.primitives import StatevectorSampler as Sampler
from qiskit.quantum_info import SparsePauliOp
# 1. let's annotate out function to convert it
# to distributed async function
# using `distribute_task` decorator
@distribute_task()
def distributed_sample(circuit: QuantumCircuit):
"""Calculates quasi dists as a distributed function."""
return Sampler().run([(circuit)]).result()[0].data.meas.get_counts()
# 2. our program will have one arguments
# `circuits` which will store list of circuits
# we want to sample in parallel.
# Let's use `get_arguments` funciton
# to access all program arguments
arguments = get_arguments()
circuits = arguments.get("circuits", [])
# 3. run our functions in a loop
# and get execution references back
function_references = [
distributed_sample(circuit)
for circuit in circuits
]
# 4. `get` function will collect all
# results from distributed functions
collected_results = get(function_references)
# 5. `save_result` will save results of program execution
# so we can access it later
save_result({
"quasi_dists": collected_results
})
Step 2: run function
from qiskit_serverless import ServerlessClient, QiskitFunction
from qiskit.circuit.random import random_circuit
client = ServerlessClient(
token="<TOKEN>",
host="<GATEWAY_ADDRESS>",
)
# create function
function = QiskitFunction(
title="Quickstart",
entrypoint="program.py",
working_dir="./src"
)
client.upload(function)
# create inputs to our program
circuits = []
for _ in range(3):
circuit = random_circuit(3, 2)
circuit.measure_all()
circuits.append(circuit)
# run program
my_function = client.get("Quickstart")
job = my_function.run(circuits=circuits)
Step 3: monitor job status
job.status()
# 'DONE'
# or get logs
job.logs()
Step 4: get results
job.result()
# {'quasi_dists': [
# {'101': 902, '011': 66, '110': 2, '111': 37, '100': 17},
# {'100': 626, '101': 267, '001': 49, '000': 82},
# {'010': 145, '100': 126, '011': 127, '001': 89, '110': 173, '111': 166, '000': 94, '101': 104}
# ]}
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