#   Copyright (c) 2020 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 fleet metric."""

import numpy as np
import paddle
import paddle.fluid as fluid
import unittest
import numpy as np
import paddle.distributed.fleet.metrics.metric as metric
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet.base.util_factory import UtilBase

paddle.enable_static()


class TestFleetMetric(unittest.TestCase):
    """Test cases for fleet metric."""

    def setUp(self):
        """Set up, set envs."""

        class FakeUtil(UtilBase):
            def __init__(self, fake_fleet):
                super(FakeUtil, self).__init__()
                self.fleet = fake_fleet

            def all_reduce(self, input, mode="sum", comm_world="worker"):
                input = np.array(input)
                input_shape = input.shape
                input_list = input.reshape(-1).tolist()

                self.fleet._barrier(comm_world)

                ans = self.fleet._all_reduce(input_list, mode)

                output = np.array(ans).reshape(input_shape)
                return output

        class FakeFleet:
            """Fake fleet only for test."""

            def __init__(self):
                """Init."""
                self.gloo = fluid.core.Gloo()
                self.gloo.set_rank(0)
                self.gloo.set_size(1)
                self.gloo.set_prefix("123")
                self.gloo.set_iface("lo")
                self.gloo.set_hdfs_store("./tmp_test_metric", "", "")
                self.gloo.init()

            def _all_reduce(self, input, mode="sum"):
                """All reduce using gloo."""
                ans = self.gloo.all_reduce(input, mode)
                return ans

            def _barrier(self, comm_world="worker"):
                """Fake barrier, do nothing."""
                pass

        self.util = FakeUtil(FakeFleet())
        fleet.util = self.util

    def test_metric_1(self):
        """Test cases for metrics."""
        train = fluid.Program()
        startup = fluid.Program()
        with fluid.program_guard(train, startup):
            t = fluid.layers.create_global_var(
                shape=[1, 1],
                value=1,
                dtype='int64',
                persistable=True,
                force_cpu=True,
            )
            t1 = fluid.layers.create_global_var(
                shape=[1, 1],
                value=1,
                dtype='int64',
                persistable=True,
                force_cpu=True,
            )
        place = fluid.CPUPlace()
        exe = fluid.Executor(place)
        scope = fluid.Scope()
        with fluid.scope_guard(scope):
            exe.run(startup)
            metric.sum(t, scope, self.util)
            metric.max(t, scope, self.util)
            metric.min(t, scope, self.util)
            metric.auc(t, t1, scope, self.util)
            metric.mae(t, t1, scope, self.util)
            metric.rmse(t, t1, scope, self.util)
            metric.mse(t, t1, scope, self.util)
            metric.acc(t, t1, scope, self.util)
            metric.sum(str(t.name))
            metric.max(str(t.name))
            metric.min(str(t.name))
            metric.auc(str(t1.name), str(t.name))
            metric.mae(str(t1.name), str(t.name))
            metric.rmse(str(t1.name), str(t.name))
            metric.mse(str(t1.name), str(t.name))
            metric.acc(str(t.name), str(t1.name))
        arr = np.array([1, 2, 3, 4])
        metric.sum(arr, util=self.util)
        metric.max(arr, util=self.util)
        metric.min(arr, util=self.util)
        arr1 = np.array([[1, 2, 3, 4]])
        arr2 = np.array([[1, 2, 3, 4]])
        arr3 = np.array([1, 2, 3, 4])
        metric.auc(arr1, arr2, util=self.util)
        metric.mae(arr, arr3, util=self.util)
        metric.rmse(arr, arr3, util=self.util)
        metric.mse(arr, arr3, util=self.util)
        metric.acc(arr, arr3, util=self.util)


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