from pydantic.dataclasses import dataclass
from ..base import BaseSamplerConfig
[docs]@dataclass
class RHVAESamplerConfig(BaseSamplerConfig):
"""RHVAESampler config class.
Parameters:
num_samples (int): The number of samples to generate. Default: 1
batch_size (int): The number of samples per batch. Batching is used to speed up
generation and avoid memory overflows. Default: 50
mcmc_steps (int): The number of MCMC steps to use in the latent space HMC sampler.
Default: 100
n_lf (int): The number of leapfrog to use in the integrator of the HMC sampler.
Default: 15
eps_lf (float): The leapfrog stepsize in the integrator of the HMC sampler. Default: 3e-2
random_start (bool): Initialization of the latent space sampler. If False, the sampler
starts the Markov chain on the metric centroids. If True , a random start is applied.
Default: False
"""
mcmc_steps_nbr: int = 100
n_lf: int = 15
eps_lf: float = 0.03
beta_zero: float = 1.0