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* Support infinite generators for training corpora Support a training corpus with an infinite generator in the `spacy train` training loop: * Revert `create_train_batches` to the state where an infinite generator can be used as the in the first epoch of exactly one epoch without resulting in a memory leak (`max_epochs != 1` will still result in a memory leak) * Move the shuffling for the first epoch into the corpus reader, renaming it to `spacy.Corpus.v2`. * Switch to training option for shuffling in memory Training loop: * Add option `training.shuffle_train_corpus_in_memory` that controls whether the corpus is loaded in memory once and shuffled in the training loop * Revert changes to `create_train_batches` and rename to `create_train_batches_with_shuffling` for use with `spacy.Corpus.v1` and a corpus that should be loaded in memory * Add `create_train_batches_without_shuffling` for a corpus that should not be shuffled in the training loop: the corpus is merely batched during training Corpus readers: * Restore `spacy.Corpus.v1` * Add `spacy.ShuffledCorpus.v1` for a corpus shuffled in memory in the reader instead of the training loop * In combination with `shuffle_train_corpus_in_memory = False`, each epoch could result in a different augmentation * Refactor create_train_batches, validation * Rename config setting to `training.shuffle_train_corpus` * Refactor to use a single `create_train_batches` method with a `shuffle` option * Only validate `get_examples` in initialize step if: * labels are required * labels are not provided * Switch back to max_epochs=-1 for streaming train corpus * Use first 100 examples for stream train corpus init * Always check validate_get_examples in initialize |
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.. | ||
cli | ||
displacy | ||
lang | ||
matcher | ||
ml | ||
pipeline | ||
tests | ||
tokens | ||
training | ||
__init__.pxd | ||
__init__.py | ||
__main__.py | ||
about.py | ||
attrs.pxd | ||
attrs.pyx | ||
compat.py | ||
default_config_pretraining.cfg | ||
default_config.cfg | ||
errors.py | ||
glossary.py | ||
kb.pxd | ||
kb.pyx | ||
language.py | ||
lexeme.pxd | ||
lexeme.pyx | ||
lookups.py | ||
morphology.pxd | ||
morphology.pyx | ||
parts_of_speech.pxd | ||
parts_of_speech.pyx | ||
pipe_analysis.py | ||
py.typed | ||
schemas.py | ||
scorer.py | ||
strings.pxd | ||
strings.pyx | ||
structs.pxd | ||
symbols.pxd | ||
symbols.pyx | ||
tokenizer.pxd | ||
tokenizer.pyx | ||
typedefs.pxd | ||
typedefs.pyx | ||
util.py | ||
vectors.pyx | ||
vocab.pxd | ||
vocab.pyx |