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134 lines
4.7 KiB
134 lines
4.7 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 os
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from datetime import datetime
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from pathlib import Path
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from typing import Any
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from typing import Dict
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from typing import List
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import jsonlines
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from . import extension
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from ..reporter import get_observations
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from ..updaters.trainer import Trainer
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from paddlespeech.s2t.utils.log import Log
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from paddlespeech.s2t.utils.mp_tools import rank_zero_only
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logger = Log(__name__).getlog()
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def load_records(records_fp):
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"""Load record files (json lines.)"""
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with jsonlines.open(records_fp, 'r') as reader:
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records = list(reader)
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return records
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class Snapshot(extension.Extension):
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"""An extension to make snapshot of the updater object inside
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the trainer. It is done by calling the updater's `save` method.
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An Updater save its state_dict by default, which contains the
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updater state, (i.e. epoch and iteration) and all the model
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parameters and optimizer states. If the updater inside the trainer
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subclasses StandardUpdater, everything is good to go.
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Parameters
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----------
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checkpoint_dir : Union[str, Path]
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The directory to save checkpoints into.
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"""
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trigger = (1, 'epoch')
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priority = -100
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default_name = "snapshot"
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def __init__(self,
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mode='latest',
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max_size: int=5,
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indicator=None,
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less_better=True,
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snapshot_on_error: bool=False):
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self.records: List[Dict[str, Any]] = []
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assert mode in ('latest', 'kbest'), mode
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if mode == 'kbest':
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assert indicator is not None
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self.mode = mode
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self.indicator = indicator
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self.less_is_better = less_better
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self.max_size = max_size
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self._snapshot_on_error = snapshot_on_error
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self._save_all = (max_size == -1)
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self.checkpoint_dir = None
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def initialize(self, trainer: Trainer):
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"""Setting up this extention."""
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self.checkpoint_dir = trainer.out / "checkpoints"
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# load existing records
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record_path: Path = self.checkpoint_dir / "records.jsonl"
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if record_path.exists():
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self.records = load_records(record_path)
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ckpt_path = self.records[-1]['path']
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logger.info(f"Loading from an existing checkpoint {ckpt_path}")
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trainer.updater.load(ckpt_path)
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def on_error(self, trainer, exc, tb):
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if self._snapshot_on_error:
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self.save_checkpoint_and_update(trainer, 'latest')
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def __call__(self, trainer: Trainer):
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self.save_checkpoint_and_update(trainer, self.mode)
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def full(self):
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"""Whether the number of snapshots it keeps track of is greater
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than the max_size."""
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return (not self._save_all) and len(self.records) > self.max_size
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@rank_zero_only
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def save_checkpoint_and_update(self, trainer: Trainer, mode: str):
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"""Saving new snapshot and remove the oldest snapshot if needed."""
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iteration = trainer.updater.state.iteration
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epoch = trainer.updater.state.epoch
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num = epoch if self.trigger[1] == 'epoch' else iteration
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path = self.checkpoint_dir / f"{num}.np"
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# add the new one
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trainer.updater.save(path)
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record = {
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"time": str(datetime.now()),
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'path': str(path.resolve()), # use absolute path
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'iteration': iteration,
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'epoch': epoch,
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'indicator': get_observations()[self.indicator]
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}
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self.records.append(record)
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# remove the earist
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if self.full():
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if mode == 'kbest':
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self.records = sorted(
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self.records,
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key=lambda record: record['indicator'],
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reverse=not self.less_is_better)
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eariest_record = self.records[0]
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os.remove(eariest_record["path"])
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self.records.pop(0)
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# update the record file
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record_path = self.checkpoint_dir / "records.jsonl"
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with jsonlines.open(record_path, 'w') as writer:
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for record in self.records:
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# jsonlines.open may return a Writer or a Reader
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writer.write(record) # pylint: disable=no-member
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