# ==============================================================================
# Copyright 2014 Intel Corporation
#
# Licensed 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
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# ==============================================================================

# daal4py SGD (Stochastic Gradient Descent) example for shared memory systems
# using Mean Squared Error objective function

from pathlib import Path

import numpy as np
from readcsv import pd_read_csv

import daal4py as d4p


def main(readcsv=pd_read_csv):
    data_path = Path(__file__).parent / "data" / "batch"
    infile = data_path / "mse.csv"
    # Read the data, let's have 3 independent variables
    data = readcsv(infile, range(3))
    dep_data = readcsv(infile, range(3, 4))
    nVectors = data.shape[0]

    # configure a MSE object
    mse_algo = d4p.optimization_solver_mse(nVectors)
    mse_algo.setup(data, dep_data)

    # configure a SGD object
    lrs = np.array([[1.0]], dtype=np.double)
    niters = 1000
    sgd_algo = d4p.optimization_solver_sgd(
        mse_algo,
        learningRateSequence=lrs,
        accuracyThreshold=0.0000001,
        nIterations=niters,
    )

    # finally do the computation
    inp = np.array([[8], [2], [1], [4]], dtype=np.double)
    res = sgd_algo.compute(inp)

    # The SGD result provides minimum and nIterations
    assert res.minimum.shape == inp.shape and res.nIterations[0][0] <= niters

    return res


if __name__ == "__main__":
    res = main()
    print("\nMinimum:\n", res.minimum)
    print("\nNumber of iterations performed:\n", res.nIterations[0][0])
    print("All looks good!")