# cython: language_level=3
# -*- coding: utf-8 -*-
# *****************************************************************************
# Copyright (c) 2016-2023, Intel Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# - Redistributions of source code must retain the above copyright notice,
#   this list of conditions and the following disclaimer.
# - Redistributions in binary form must reproduce the above copyright notice,
#   this list of conditions and the following disclaimer in the documentation
#   and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
# THE POSSIBILITY OF SUCH DAMAGE.
# *****************************************************************************

"""Example 10.

This example shows simple usage of the DPNP
in combination with dpctl.

"""

import time

import numpy

import dpnp


def run(executor, size, test_type, repetition):
    x = executor.reshape(
        executor.arange(size * size, dtype=test_type), (size, size)
    )

    times = []
    for _ in range(repetition):
        start_time = time.perf_counter()
        result = executor.sum(x)
        end_time = time.perf_counter()
        times.append(end_time - start_time)

    return numpy.median(times), result


def get_dtypes():
    _dtypes_list = [numpy.int32, numpy.int64, numpy.float32]
    device = dpctl.select_default_device()
    if device.has_aspect_fp64:
        _dtypes_list.append(numpy.float64)
    return _dtypes_list


def example():
    test_repetition = 5
    for test_type in get_dtypes():
        type_name = numpy.dtype(test_type).name
        print(
            f"...Test data type is {type_name}, each test repetitions {test_repetition}"
        )

        for size in [64, 128, 256, 512, 1024, 2048, 4096]:
            time_numpy, result_numpy = run(
                numpy, size, test_type, test_repetition
            )
            time_dpnp, result_dpnp = run(dpnp, size, test_type, test_repetition)

            if result_dpnp == result_numpy:
                verification = True
            else:
                verification = f"({result_dpnp} != {result_numpy})"

            msg = f"type:{type_name}:N:{size:4}:NumPy:{time_numpy:.3e}:DPNP:{time_dpnp:.3e}"
            msg += f":ratio:{time_numpy/time_dpnp:6.2f}:verification:{verification}"
            print(msg)


if __name__ == "__main__":
    try:
        import dpctl

        with dpctl.device_context("opencl:gpu") as gpu_queue:
            gpu_queue.get_sycl_device().print_device_info()
            example()

    except ImportError:
        example()
