blob: 3f2920eac4c330ad6c0d8e9f26e7260cfaa6c5e4 [file]
# -------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# 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
#
# 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.
#
# -------------------------------------------------------------
import logging
from systemds.context import SystemDSContext
from systemds.examples.tutorials.mnist import DataManager
from systemds.operator.algorithm import multiLogReg, multiLogRegPredict
d = DataManager()
with SystemDSContext() as sds:
# Train Data
X = sds.from_numpy(d.get_train_data().reshape((60000, 28 * 28)))
Y = sds.from_numpy(d.get_train_labels()) + 1.0
bias = multiLogReg(X, Y, tol=0.0001, verbose=False)
# Test data
Xt = sds.from_numpy(d.get_test_data().reshape((10000, 28 * 28)))
Yt = sds.from_numpy(d.get_test_labels()) + 1.0
[_, _, acc] = multiLogRegPredict(Xt, bias, Y=Yt).compute()
logging.info(acc)