dygraph_fleet_api.py

# Copyright (c) 2022 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.

from __future__ import print_function

import unittest
import random
import numpy as np
import os
import shutil

import paddle
import paddle.nn as nn
from paddle.fluid import core
import datetime
from datetime import timedelta
import paddle.fluid.core as core
from paddle.fluid.framework import _test_eager_guard
from paddle.fluid.dygraph.parallel import ParallelEnv


class TestDygraphFleetAPI(unittest.TestCase):
    def setUp(self):
        paddle.seed(2022)
        random.seed(2022)
        np.random.seed(2022)
        self.config()

    def config(self):
        self.dtype = "float32"
        self.shape = (2, 10, 5)

    def test_dygraph_fleet_api(self):
        import paddle.distributed.fleet as fleet
        import paddle.distributed as dist
        strategy = fleet.DistributedStrategy()
        strategy.amp = True
        strategy.recompute = True
        fleet.init(is_collective=True, strategy=strategy)
        net = paddle.nn.Sequential(
            paddle.nn.Linear(10, 1), paddle.nn.Linear(1, 2))
        net = dist.fleet.distributed_model(net)
        data = np.random.uniform(-1, 1, [30, 10]).astype('float32')
        data = paddle.to_tensor(data)
        net(data)


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