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# Licensed to the Apache Software Foundation (ASF) under one
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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
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# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
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import os
import shutil
import sys
import unittest
import numpy as np
import pandas as pd
from systemds.context import SystemDSContext
from systemds.operator.algorithm import hyperband
class TestHyperband(unittest.TestCase):
sds: SystemDSContext = None
np.random.seed(42)
X_train = np.random.rand(50, 10)
y_train = np.sum(X_train, axis=1, keepdims=True) + np.random.rand(50, 1)
X_val = np.random.rand(50, 10)
y_val = np.sum(X_val, axis=1, keepdims=True) + np.random.rand(50, 1)
params = 'list("reg", "tol", "maxi")'
min_max_params = [[0, 20], [0.0001, 0.1], [5, 10]]
param_ranges = np.array(min_max_params)
@classmethod
def setUpClass(cls):
cls.sds = SystemDSContext(capture_stdout=True, logging_level=50)
@classmethod
def tearDownClass(cls):
cls.sds.close()
def tearDown(self):
pass
def test_hyperband(self):
x_train = self.sds.from_numpy(self.X_train)
y_train = self.sds.from_numpy(self.y_train)
x_val = self.sds.from_numpy(self.X_val)
y_val = self.sds.from_numpy(self.y_val)
paramRanges = self.sds.from_numpy(self.param_ranges)
params = self.params
[best_weights_mat, opt_hyper_params_df] = hyperband(
X_train=x_train,
y_train=y_train,
X_val=x_val,
y_val=y_val,
params=params,
paramRanges=paramRanges,
verbose=False,
).compute()
self.assertTrue(isinstance(best_weights_mat, np.ndarray))
self.assertTrue(best_weights_mat.shape[0] == self.X_train.shape[1])
self.assertTrue(best_weights_mat.shape[1] == self.y_train.shape[1])
self.assertTrue(isinstance(opt_hyper_params_df, pd.DataFrame))
self.assertTrue(opt_hyper_params_df.shape[1] == 1)
for i, hyper_param in enumerate(opt_hyper_params_df.values.flatten().tolist()):
self.assertTrue(
self.min_max_params[i][0] <= hyper_param <= self.min_max_params[i][1]
)
if __name__ == "__main__":
unittest.main(exit=False)