def test_save_restore(tmpdir):
space = FeatureSpace({
'a': Feature(DiscreteBox([0, 12])),
'b': Feature(Box((0, 1)), lengthDomain=DiscreteBox((1, 2)))
})
sampler = FeatureSampler.simulatedAnnealingSamplerFor(space, sa_params)
checkSaveRestore(sampler, tmpdir, iterations=10)
def test_save_restore(tmpdir):
space = FeatureSpace({
'a': Feature(DiscreteBox([0, 12])),
'b': Feature(Box((0, 1)), lengthDomain=DiscreteBox((1, 2)))
})
halton_params = DotMap(sample_index=0, bases_skipped=0)
sampler = FeatureSampler.haltonSamplerFor(space, halton_params)
checkSaveRestore(sampler, tmpdir)
def test_save_restore(tmpdir):
space = FeatureSpace({
'a': Feature(DiscreteBox([0, 12])),
'b': Feature(Box((0, 1)), lengthDomain=DiscreteBox((1, 2)))
})
bo_params = DotMap(init_num=2)
sampler = FeatureSampler.bayesianOptimizationSamplerFor(space, bo_params)
checkSaveRestore(sampler, tmpdir)
def test_save_restore(tmpdir):
space = FeatureSpace({
'a':
Feature(DiscreteBox([0, 12])),
'b':
Feature(Box((0, 1))),
'c':
Feature(Box((0, 1), (-1, 1)), lengthDomain=DiscreteBox((0, 1)))
})
ce_params = DotMap(alpha=0.9, thres=0)
ce_params.cont.buckets = 5
ce_params.cont.dist = None
ce_params.disc.dist = None
sampler = FeatureSampler.crossEntropySamplerFor(space, ce_params)
checkSaveRestore(sampler, tmpdir, iterations=30)
def test_active_save_restore(tmpdir):
sampler = ScenicSampler.fromScenicCode(
'param verifaiSamplerType = "halton"\n'
'ego = Object at VerifaiRange(-1, 1) @ 0',
maxIterations=1)
checkSaveRestore(sampler, tmpdir)
def test_save_restore(tmpdir):
sampler = ScenicSampler.fromScenicCode('ego = Object at Range(-1, 1) @ 0',
maxIterations=1)
checkSaveRestore(sampler, tmpdir)