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52 lines
1.7 KiB
52 lines
1.7 KiB
# Copyright (c) 2021 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 shutil
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from itertools import count
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from paddle import nn
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from paddle.optimizer import Adam
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from parakeet.training.extensions.snapshot import Snapshot
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from parakeet.training.trainer import Trainer
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from parakeet.training.updater import StandardUpdater
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def test_snapshot():
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model = nn.Linear(3, 4)
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optimizer = Adam(parameters=model.parameters())
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# use a simplest iterable object as dataloader
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dataloader = count()
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# hack the training proecss: training does nothing except increse iteration
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updater = StandardUpdater(model, optimizer, dataloader=dataloader)
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updater.update_core = lambda x: None
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trainer = Trainer(
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updater, stop_trigger=(1000, 'iteration'), out='temp_test_snapshot')
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shutil.rmtree(trainer.out, ignore_errors=True)
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snap = Snapshot(max_size=5)
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trigger = (10, 'iteration')
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trainer.extend(snap, name='snapshot', trigger=trigger, priority=0)
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trainer.run()
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checkpoint_dir = trainer.out / "checkpoints"
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snapshots = sorted(list(checkpoint_dir.glob("snapshot_iter_*.pdz")))
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for snap in snapshots:
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print(snap)
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assert len(snapshots) == 5
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shutil.rmtree(trainer.out)
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