wehub-resource-sync
77 lines
3.0 KiB
Python
77 lines
3.0 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import shutil
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import unittest
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import numpy as np
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from test_dist_sparse_load_ps0 import SparseLoadOp
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import paddle
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from paddle import base
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from paddle.distributed.fleet import fleet
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from paddle.distributed.fleet.base import role_maker
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@unittest.skip(reason="Skip unstable ut, need rewrite with new implement")
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class TestSparseLoadOpCase2(SparseLoadOp):
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def test_2ps_0_load(self):
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# init No.1 server env
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env = {}
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env["PADDLE_PSERVERS_IP_PORT_LIST"] = "127.0.0.1:4001,127.0.0.1:4002"
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env["PADDLE_TRAINERS_NUM"] = str(2)
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env["TRAINING_ROLE"] = "PSERVER"
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env["PADDLE_PORT"] = "4002"
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env["POD_IP"] = "127.0.0.1"
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for k, v in env.items():
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os.environ[k] = str(v)
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"""
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array([[0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],
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[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
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[0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2],
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[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
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[0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4],
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[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
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[0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6],
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[0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7],
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[0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8],
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[0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9]])
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"""
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emb_array = np.arange(0, 1, 0.1).repeat(10).reshape(10, 10)
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fc_array = np.arange(0, 1, 0.1).repeat(10).reshape(10, 10)
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model_path = self.save_origin_model(emb_array, fc_array)
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startup_program = base.framework.Program()
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test_program = base.framework.Program()
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role = role_maker.PaddleCloudRoleMaker()
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fleet.init(role)
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loss = self.net(emb_array, fc_array)
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strategy = paddle.distributed.fleet.DistributedStrategy()
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strategy.a_sync = True
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optimizer = paddle.optimizer.Adam(1e-3)
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optimizer = fleet.distributed_optimizer(optimizer, strategy)
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optimizer.minimize(loss)
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fleet.init_server(model_path)
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emb = np.array(
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base.global_scope().find_var("embedding.block1").get_tensor()
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)
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assert emb.all() == emb_array[1::2].all()
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shutil.rmtree(model_path)
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if __name__ == "__main__":
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paddle.enable_static()
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unittest.main()
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