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Paddle/python/paddle/fluid/tests/unittests/test_fleet_metric.py

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4.4 KiB

# 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."""
from __future__ import print_function
import numpy as np
import paddle
import paddle.fluid as fluid
import os
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(UtilBase, 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()