def sample(n_samps, n_iter, epsilon, path):
if not os.path.exists(path):
os.makedirs(path)
path=path+"/svgd"
prior = multivariate_normal(np.zeros((num_dimensions)), 1e3 * np.eye(num_dimensions))
x0 = prior.rvs(n_samps)
start = time()
samples = SVGD().update(x0, dlnpdf, n_iter=n_iter, stepsize=epsilon, path=path)
end = time()
np.savez(path, samples=samples, wallclocktime=end-start, nfevals=dlnpdf.counter, true_means=means, true_covs=covs)
print("done")
def sample(n_samps, n_iter, epsilon, path):
if path is not None:
dirname = os.path.dirname(path)
if not os.path.exists(dirname):
os.makedirs(dirname)
prior = multivariate_normal(np.zeros((num_dimensions)), np.eye(num_dimensions))
x0 = prior.rvs(n_samps)
start = time()
samples = SVGD().update(x0, dlnpdf, n_iter=n_iter, stepsize=epsilon, path=path)
end = time()
np.savez(path, samples=samples, wallclocktime=end-start, nfevals=dlnpdf.counter)
print("done")