blob: 25832b648fc133bab8a5bb45950f57eec1b2146a [file]
# -------------------------------------------------------------
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
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# -------------------------------------------------------------
import io
import json
import os
import shutil
import sys
import unittest
import numpy as np
from systemds.context import SystemDSContext
os.environ['SYSDS_QUIET'] = "1"
dim = 3
m1 = np.asarray([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.int16)
m2 = np.asarray([[2, 2, 2], [3, 3, 3], [4, 4, 4]], dtype=np.int16)
tempdir = "./tests/federated/tmp/test_federated_aggregations_noHeader/"
mtd = {"format": "csv", "header": False, "rows": dim,
"cols": dim, "data_type": "matrix", "value_type": "double"}
# Create the testing directory if it does not exist.
if not os.path.exists(tempdir):
os.makedirs(tempdir)
# Save data files for the Federated workers.
np.savetxt(tempdir + "m1.csv", m1, delimiter=",",fmt='%d')
with io.open(tempdir + "m1.csv.mtd", "w", encoding="utf-8") as f:
f.write(json.dumps(mtd, ensure_ascii=False))
np.savetxt(tempdir + "m2.csv", m2, delimiter=",",fmt='%d')
with io.open(tempdir + "m2.csv.mtd", "w", encoding="utf-8") as f:
f.write(json.dumps(mtd, ensure_ascii=False))
# Federated workers + file locations
fed1 = "localhost:8001/" + tempdir + "m1.csv"
fed2 = "localhost:8002/" + tempdir + "m2.csv"
class TestFederatedAggFn(unittest.TestCase):
sds: SystemDSContext = None
@classmethod
def setUpClass(cls):
cls.sds = SystemDSContext()
@classmethod
def tearDownClass(cls):
cls.sds.close()
def test_equals(self):
f_m = (
self.sds.federated(
[fed1],
[([0, 0], [dim, dim])])
.compute()
)
self.assertTrue(np.allclose(f_m, m1))
def test_sum3(self):
# [[m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]]
f_m_a = (
self.sds.federated(
[fed1, fed2],
[([0, 0], [dim, dim]), ([0, dim], [dim, dim * 2])])
.sum()
.compute()
)
m1_m2 = m1.sum() + m2.sum()
self.assertAlmostEqual(f_m_a, m1_m2)
def test_sum1(self):
f_m1 = (
self.sds.federated(
[fed1],
[([0, 0], [dim, dim])])
.sum()
.compute()
)
m1_r = m1.sum()
self.assertAlmostEqual(f_m1, m1_r)
def test_sum2(self):
f_m2 = (
self.sds.federated(
[fed2],
[([0, 0], [dim, dim])])
.sum()
.compute()
)
m2_r = m2.sum()
self.assertAlmostEqual(f_m2, m2_r)
def test_sum3(self):
# [[m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]]
f_m1_m2 = (
self.sds.federated(
[fed1, fed2],
[([0, 0], [dim, dim]), ([0, dim], [dim, dim * 2])])
.sum()
.compute()
)
m1_m2 = np.concatenate((m1, m2), axis=1).sum()
self.assertAlmostEqual(f_m1_m2, m1_m2)
def test_sum4(self):
# [[m1,m1,m1,m1,m1]
# [m1,m1,m1,m1,m1]
# [m1,m1,m1,m1,m1]
# [m1,m1,m1,m1,m1]
# [m1,m1,m1,m1,m1]
# [m2,m2,m2,m2,m2]
# [m2,m2,m2,m2,m2]
# [m2,m2,m2,m2,m2]
# [m2,m2,m2,m2,m2]
# [m2,m2,m2,m2,m2]]
f_m1_m2 = (
self.sds.federated(
[fed1, fed2],
[([0, 0], [dim, dim]), ([dim, 0], [dim * 2, dim])])
.sum()
.compute()
)
m1_m2 = np.concatenate((m1, m2)).sum()
self.assertAlmostEqual(f_m1_m2, m1_m2)
# -----------------------------------
# The rest of the tests are
# Extended functionality not working Yet
# -----------------------------------
def test_sum5(self):
# [[m1,m1,m1,m1,m1, 0, 0, 0, 0, 0]
# [m1,m1,m1,m1,m1, 0, 0, 0, 0, 0]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [m1,m1,m1,m1,m1,m2,m2,m2,m2,m2]
# [ 0, 0, 0, 0, 0,m2,m2,m2,m2,m2]
# [ 0, 0, 0, 0, 0,m2,m2,m2,m2,m2]]
f_m_a = (
self.sds.federated(
[fed1, fed2],
[([0, 0], [dim, dim]), ([2, dim], [dim + 2, dim * 2])])
.sum()
.compute()
)
m1_m2 = m1.sum() + m2.sum()
self.assertAlmostEqual(f_m_a, m1_m2)
def test_sum8(self):
# [[ 0, 0, 0, 0, 0, 0, 0, 0]
# [ 0, 0, 0, 0, 0, 0, 0, 0]
# [ 0, 0, 0,m1,m1,m1,m1,m1]
# [ 0, 0, 0,m1,m1,m1,m1,m1]
# [ 0, 0, 0,m1,m1,m1,m1,m1]
# [ 0, 0, 0,m1,m1,m1,m1,m1]
# [ 0, 0, 0,m1,m1,m1,m1,m1]]
f_m_a = (
self.sds.federated(
[fed1],
[([2, 3], [dim + 2, dim + 3])])
.sum()
.compute()
)
m = m1.sum()
self.assertAlmostEqual(f_m_a, m)
if __name__ == "__main__":
unittest.main(exit=False)