i~RSrSSKJrJr SSKJr SSKJr SSKJ r "SS\ 5r g ) zQiskit Runtime batch mode.)OptionalUnion) BackendV2)QiskitRuntimeService)Sessionc ^\rSrSrSrS SS.S\S\\\\ 4S\\ 4U4Sjjjjr SS.S\\ S \\ 4S jjr S r U=r$) Batcha Class for running jobs in batch execution mode. The ``batch`` mode is designed to efficiently perform experiments that comprise multiple independent jobs. Using the ``batch`` mode provides the following benefits: - The jobs' classical computation, such as compilation, is run in parallel. Thus, running multiple jobs in a batch is significantly faster than running them serially. - There is usually minimal delay between job, which can help avoid drift. - If you partition your workload into multiple jobs and run them in ``batch`` mode, you can get results from individual jobs, which makes them more flexible to work with. For example, if a job's results do not meet your expectations, you can cancel the remaining jobs, or simply re-submit that individual job and avoid re-running the entire workload. Batch mode can shorten processing time if all jobs are provided at the outset. If you want to submit iterative jobs, use ``session`` mode instead. You can open a Qiskit Runtime batch by using this ``Batch`` class, then submit jobs to one or more primitives. For example:: import numpy as np from qiskit.circuit.library import IQP from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager from qiskit.quantum_info import random_hermitian from qiskit_ibm_runtime import QiskitRuntimeService, SamplerV2 as Sampler, Batch n_qubits = 127 service = QiskitRuntimeService() backend = service.least_busy(operational=True, simulator=False, min_num_qubits=n_qubits) rng = np.random.default_rng() mats = [np.real(random_hermitian(n_qubits, seed=rng)) for _ in range(30)] circuits = [IQP(mat) for mat in mats] for circuit in circuits: circuit.measure_all() pm = generate_preset_pass_manager(backend=backend, optimization_level=1) isa_circuits = pm.run(circuits) max_circuits = 10 all_partitioned_circuits = [] for i in range(0, len(isa_circuits), max_circuits): all_partitioned_circuits.append(isa_circuits[i : i + max_circuits]) jobs = [] start_idx = 0 with Batch(backend=backend): sampler = Sampler() for partitioned_circuits in all_partitioned_circuits: job = sampler.run(partitioned_circuits) jobs.append(job) For more details, check the "`Run jobs in a batch `_" page. T) create_newbackendmax_timer c">[TU]XUS9 g)agBatch constructor. Args: backend: Instance of ``Backend`` class. max_time: Maximum amount of time a runtime session can be open before being forcibly closed. Can be specified as seconds (int) or a string like "2h 30m 40s". This value must be less than the `system imposed maximum `_. create_new: If True, the POST session API endpoint will be called to create a new session. Prevents creating a new session when ``from_id()`` is called. Raises: ValueError: If an input value is invalid. )r rr N)super__init__)selfr rr __class__s R/home/james-whalen/.local/lib/python3.13/site-packages/qiskit_ibm_runtime/batch.pyrBatch.__init__Us0  Sreturnc$[UR[5(aqU(ajURRUR5R UR 5URURS5nURS5$g)zCreate a session.batchidN) isinstance_servicer_get_api_client _instancecreate_sessionr _max_timeget)rr sessions r_create_sessionBatch._create_sessionosd dmm%9 : :zmm33DNNCRR G;;t$ $r)N)__name__ __module__ __qualname____firstlineno____doc__rrrintstrboolrr#__static_attributes__ __classcell__)rs@rr r s|;@/3T &* TT5c?+T TN TT4?CXd^xPS}rr N) r*typingrrqiskit.providers.backendrqiskit_ibm_runtimerr"rr r%rrr3s$!".3_G_r