qat.plugins.SPSAMinimizePlugin

class qat.plugins.SPSAMinimizePlugin(x0=None, collective=False, binding_args=None, **kwargs)

A variational minimizer based on the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm.

This is a particularization of the Optimizer class.

Parameters

x0 (np.array, optional) – Initial parameters values. If set to None, the initial parameters will be randomly chosen.
binding_args (dict, optional) – arguments to bind job variables (see Optimizer documentation). Defaults to None.
maxiter (int, optional) – maximal number of iterations. Defaults to 100.
a (int, optional) – \(a\) parameter. Defaults to 1.
A (int, optional) – \(A\) parameter. Defaults to 10.
alpha (float, optional) – \(\alpha\) parameter. Defaults to 0.602.
c (float, optional) – \(c\) parameter. Defaults to 0.01.
gamma (float, optional) – \(\gamma\) parameter. Defaults to 0.101.
precision (float, optional) – stop after ‘stop_condition’ consecutive times when difference between two successive function evalutions are lower than precision. Defaults to 1e-4.
stop_condition (int, optional) – see ‘precision’. Defaults to 5.
a_calibration (bool, optional) – whether to calibrate a param. Defaults to False
n_calibrations (int, optional) – Defaults to 25.
seed (int, optional) – seed for random number generator. Defaults to None.

References

compile(batch: Batch) → Batch

Loops a batch through all the plugins present inside the QPU.

Parameters: batch (Batch) – a batch of jobs. If a single job is provided, the job is embedded into a Batch, compiled, and the first result is returned.
Returns: a batch of jobs
Return type: (Batch)