#   copyright (c) 2019 paddlepaddle authors. all rights reserved.
#
# 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
# limitations under the license.
"""
Test LightNAS.
"""
import sys
import unittest
import paddle.fluid as fluid
from paddle.fluid.contrib.slim.core import Compressor
sys.path.append("./light_nas")
from light_nas_space import LightNASSpace


class TestLightNAS(unittest.TestCase):
    """
    Test LightNAS.
    """

    def test_compression(self):
        """
        Test LightNAS.
        """
        # Update compress.yaml
        lines = list()
        fid = open('./light_nas/compress.yaml')
        for line in fid:
            if 'target_latency' in line:
                lines.append('        target_latency: 0\n')
            else:
                lines.append(line)
        fid.close()
        fid = open('./light_nas/compress.yaml', 'w')
        for line in lines:
            fid.write(line)
        fid.close()

        # Begin test
        if not fluid.core.is_compiled_with_cuda():
            return

        space = LightNASSpace()

        startup_prog, train_prog, test_prog, train_metrics, test_metrics, train_reader, test_reader = space.create_net(
        )
        train_cost, train_acc1, train_acc5, global_lr = train_metrics
        test_cost, test_acc1, test_acc5 = test_metrics

        place = fluid.CUDAPlace(0)
        exe = fluid.Executor(place)
        exe.run(startup_prog)

        val_fetch_list = [('acc_top1', test_acc1.name),
                          ('acc_top5', test_acc5.name)]
        train_fetch_list = [('loss', train_cost.name)]

        com_pass = Compressor(
            place,
            fluid.global_scope(),
            train_prog,
            train_reader=train_reader,
            train_feed_list=None,
            train_fetch_list=train_fetch_list,
            eval_program=test_prog,
            eval_reader=test_reader,
            eval_feed_list=None,
            eval_fetch_list=val_fetch_list,
            train_optimizer=None,
            search_space=space)
        com_pass.config('./light_nas/compress.yaml')
        eval_graph = com_pass.run()

    def test_compression_with_target_latency(self):
        """
        Test LightNAS with target_latency.
        """
        # Update compress.yaml
        lines = list()
        fid = open('./light_nas/compress.yaml')
        for line in fid:
            if 'target_latency' in line:
                lines.append('        target_latency: 1\n')
            else:
                lines.append(line)
        fid.close()
        fid = open('./light_nas/compress.yaml', 'w')
        for line in lines:
            fid.write(line)
        fid.close()

        # Begin test
        if not fluid.core.is_compiled_with_cuda():
            return

        space = LightNASSpace()

        startup_prog, train_prog, test_prog, train_metrics, test_metrics, train_reader, test_reader = space.create_net(
        )
        train_cost, train_acc1, train_acc5, global_lr = train_metrics
        test_cost, test_acc1, test_acc5 = test_metrics

        place = fluid.CUDAPlace(0)
        exe = fluid.Executor(place)
        exe.run(startup_prog)

        val_fetch_list = [('acc_top1', test_acc1.name),
                          ('acc_top5', test_acc5.name)]
        train_fetch_list = [('loss', train_cost.name)]

        com_pass = Compressor(
            place,
            fluid.global_scope(),
            train_prog,
            train_reader=train_reader,
            train_feed_list=None,
            train_fetch_list=train_fetch_list,
            eval_program=test_prog,
            eval_reader=test_reader,
            eval_feed_list=None,
            eval_fetch_list=val_fetch_list,
            train_optimizer=None,
            search_space=space)
        com_pass.config('./light_nas/compress.yaml')
        eval_graph = com_pass.run()


if __name__ == '__main__':
    unittest.main()