def demo_branin(steps=20, random_steps=5, cv=5, disable_auto_plot=False):
conn = Connection(server_address)
optimizers = ["RandomSearch", "BayOpt"]
optimizer_arguments = [{}, {"initial_random_runs": random_steps}]
param_defs = {
"x": {
"type": "MinMaxNumericParamDef",
"lower_bound": -5,
"upper_bound": 10
},
"y": {
"type": "MinMaxNumericParamDef",
"lower_bound": 0,
"upper_bound": 15
},
}
exp_ids = []
for i, o in enumerate(optimizers):
exp_id = conn.init_experiment(
o,
o,
param_defs,
minimization=True,
optimizer_arguments=optimizer_arguments[i]
) #{"multiprocessing": "none"})
exp_ids.append(exp_id)
print("Initialized all optimizers.")
for i in range(steps * cv):
if i > 0 and i % 10 == 0:
print("finished %i" % i)
for e_id in exp_ids:
single_branin_evaluation_step(conn, e_id)
if z == "A":
result *= 10
if z == "B":
result *= 0.8
if result > 10:
return math.log(result, 10) * 10
else:
return result
#app.run()
start_time = time.time()
server_address = "http://localhost:5000"
conn = Connection(server_address=server_address)
param_defs = {
"x": pd.MinMaxNumericParamDef(-5, 10),
"y": pd.MinMaxNumericParamDef(0, 15)
#, "z": pd.NominalParamDef(["A", "B", "C"])
}
pd_dict = param_defs_to_dict(param_defs)
optimizer_arguments = {
"initial_random_runs": 5,
"acquisition_hyperparams": {},
"num_gp_restarts": 5,
#"acquisition": "ExpectedImprovement", #TODO string/gfunction translation?
"kernel_params": {},
"kernel": "matern52",
