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102 lines
3.4 KiB
102 lines
3.4 KiB
3 years ago
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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 deepspeech.training.updaters.trainer import Trainer
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from deepspeech.training.extensions import extension
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from deepspeech.utils.mp_tools import rank_zero_only
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from deepspeech.utils.log import Log
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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, max_size: int=5, snapshot_on_error: bool=False):
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self.records: List[Dict[str, Any]] = []
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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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logger.debug("Loading from an existing checkpoint dir")
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self.records = load_records(record_path)
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trainer.updater.load(self.records[-1]['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)
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def __call__(self, trainer: Trainer):
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self.save_checkpoint_and_update(trainer)
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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):
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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] is 'epoch' else iteration
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path = self.checkpoint_dir / f"{num}.pdz"
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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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}
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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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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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