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Merge pull request #6209 from svlandeg/feature/doc-updates

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Ines Montani 2020-10-06 10:22:18 +02:00 committed by GitHub
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2
spacy/cli/_util.py
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@ -278,7 +278,7 @@ def show_validation_error(
"fill-config' command to fill in all the defaults, if possible:", "fill-config' command to fill in all the defaults, if possible:",
spaced=True, spaced=True,
) )
print(f"{COMMAND} init fill-config {config_path} --base {config_path}\n") print(f"{COMMAND} init fill-config {config_path} {config_path} \n")
sys.exit(1) sys.exit(1)
except InterpolationError as e: except InterpolationError as e:
msg.fail("Config validation error", e, exits=1) msg.fail("Config validation error", e, exits=1)

11
website/docs/api/cli.md
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@ -300,17 +300,16 @@ $ python -m spacy debug config [config_path] [--code] [--show-functions] [--show
``` ```
✘ Config validation error ✘ Config validation error
dropout field required
optimizer field required
optimize extra fields not permitted
training -> dropout field required {'seed': 0, 'accumulate_gradient': 1, 'dev_corpus': 'corpora.dev', 'train_corpus': 'corpora.train', 'gpu_allocator': None, 'patience': 1600, 'max_epochs': 0, 'max_steps': 20000, 'eval_frequency': 200, 'frozen_components': [], 'optimize': None, 'before_to_disk': None, 'batcher': {'@batchers': 'spacy.batch_by_words.v1', 'discard_oversize': False, 'tolerance': 0.2, 'get_length': None, 'size': {'@schedules': 'compounding.v1', 'start': 100, 'stop': 1000, 'compound': 1.001, 't': 0.0}}, 'logger': {'@loggers': 'spacy.ConsoleLogger.v1', 'progress_bar': False}, 'score_weights': {'tag_acc': 0.5, 'dep_uas': 0.25, 'dep_las': 0.25, 'sents_f': 0.0}}
training -> optimizer field required
training -> optimize extra fields not permitted
{'vectors': 'en_vectors_web_lg', 'seed': 0, 'accumulate_gradient': 1, 'init_tok2vec': None, 'raw_text': None, 'patience': 1600, 'max_epochs': 0, 'max_steps': 20000, 'eval_frequency': 200, 'frozen_components': [], 'optimize': None, 'batcher': {'@batchers': 'spacy.batch_by_words.v1', 'discard_oversize': False, 'tolerance': 0.2, 'get_length': None, 'size': {'@schedules': 'compounding.v1', 'start': 100, 'stop': 1000, 'compound': 1.001, 't': 0.0}}, 'corpus': {'train': {'@readers': 'spacy.Corpus.v1', 'path': '', 'max_length': 0, 'gold_preproc': False, 'limit': 0}, 'dev': {'@readers': 'spacy.Corpus.v1', 'path': '', 'max_length': 0, 'gold_preproc': False, 'limit': 0}} 'score_weights': {'tag_acc': 0.5, 'dep_uas': 0.25, 'dep_las': 0.25, 'sents_f': 0.0}}
If your config contains missing values, you can run the 'init fill-config' If your config contains missing values, you can run the 'init fill-config'
command to fill in all the defaults, if possible: command to fill in all the defaults, if possible:
python -m spacy init fill-config tmp/starter-config_invalid.cfg --base tmp/starter-config_invalid.cfg python -m spacy init fill-config tmp/starter-config_invalid.cfg tmp/starter-config_invalid.cfg
``` ```
</Accordion> </Accordion>

18
website/docs/api/data-formats.md
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@ -181,20 +181,20 @@ This section defines settings and controls for the training and evaluation
process that are used when you run [`spacy train`](/api/cli#train). process that are used when you run [`spacy train`](/api/cli#train).
| Name | Description | | Name | Description |
| --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `accumulate_gradient` | Whether to divide the batch up into substeps. Defaults to `1`. ~~int~~ | | `accumulate_gradient` | Whether to divide the batch up into substeps. Defaults to `1`. ~~int~~ |
| `batcher` | Callable that takes an iterator of [`Doc`](/api/doc) objects and yields batches of `Doc`s. Defaults to [`batch_by_words`](/api/top-level#batch_by_words). ~~Callable[[Iterator[Doc], Iterator[List[Doc]]]]~~ | | `batcher` | Callable that takes an iterator of [`Doc`](/api/doc) objects and yields batches of `Doc`s. Defaults to [`batch_by_words`](/api/top-level#batch_by_words). ~~Callable[[Iterator[Doc], Iterator[List[Doc]]]]~~ |
| `before_to_disk` | Optional callback to modify `nlp` object right before it is saved to disk during and after training. Can be used to remove or reset config values or disable components. Defaults to `null`. ~~Optional[Callable[[Language], Language]]~~ | | `before_to_disk` | Optional callback to modify `nlp` object right before it is saved to disk during and after training. Can be used to remove or reset config values or disable components. Defaults to `null`. ~~Optional[Callable[[Language], Language]]~~ |
| `dev_corpus` | Dot notation of the config location defining the dev corpus. Defaults to `corpora.dev`. ~~str~~ | | `dev_corpus` | Dot notation of the config location defining the dev corpus. Defaults to `corpora.dev`. ~~str~~ |
| `dropout` | The dropout rate. Defaults to `0.1`. ~~float~~ | | `dropout` | The dropout rate. Defaults to `0.1`. ~~float~~ |
| `eval_frequency` | How often to evaluate during training (steps). Defaults to `200`. ~~int~~ | | `eval_frequency` | How often to evaluate during training (steps). Defaults to `200`. ~~int~~ |
| `frozen_components` | Pipeline component names that are "frozen" and shouldn't be updated during training. See [here](/usage/training#config-components) for details. Defaults to `[]`. ~~List[str]~~ | | `frozen_components` | Pipeline component names that are "frozen" and shouldn't be initialized or updated during training. See [here](/usage/training#config-components) for details. Defaults to `[]`. ~~List[str]~~ |
| `gpu_allocator` | Library for cupy to route GPU memory allocation to. Can be `"pytorch"` or `"tensorflow"`. Defaults to variable `${system.gpu_allocator}`. ~~str~~ | | `gpu_allocator` | Library for cupy to route GPU memory allocation to. Can be `"pytorch"` or `"tensorflow"`. Defaults to variable `${system.gpu_allocator}`. ~~str~~ |
| `logger` | Callable that takes the `nlp` and stdout and stderr `IO` objects, sets up the logger, and returns two new callables to log a training step and to finalize the logger. Defaults to [`ConsoleLogger`](/api/top-level#ConsoleLogger). ~~Callable[[Language, IO, IO], [Tuple[Callable[[Dict[str, Any]], None], Callable[[], None]]]]~~ |
| `max_epochs` | Maximum number of epochs to train for. Defaults to `0`. ~~int~~ | | `max_epochs` | Maximum number of epochs to train for. Defaults to `0`. ~~int~~ |
| `max_steps` | Maximum number of update steps to train for. Defaults to `20000`. ~~int~~ | | `max_steps` | Maximum number of update steps to train for. Defaults to `20000`. ~~int~~ |
| `optimizer` | The optimizer. The learning rate schedule and other settings can be configured as part of the optimizer. Defaults to [`Adam`](https://thinc.ai/docs/api-optimizers#adam). ~~Optimizer~~ | | `optimizer` | The optimizer. The learning rate schedule and other settings can be configured as part of the optimizer. Defaults to [`Adam`](https://thinc.ai/docs/api-optimizers#adam). ~~Optimizer~~ |
| `patience` | How many steps to continue without improvement in evaluation score. Defaults to `1600`. ~~int~~ | | `patience` | How many steps to continue without improvement in evaluation score. Defaults to `1600`. ~~int~~ |
| `raw_text` | Optional path to a jsonl file with unlabelled text documents for a [rehearsal](/api/language#rehearse) step. Defaults to variable `${paths.raw}`. ~~Optional[str]~~ |
| `score_weights` | Score names shown in metrics mapped to their weight towards the final weighted score. See [here](/usage/training#metrics) for details. Defaults to `{}`. ~~Dict[str, float]~~ | | `score_weights` | Score names shown in metrics mapped to their weight towards the final weighted score. See [here](/usage/training#metrics) for details. Defaults to `{}`. ~~Dict[str, float]~~ |
| `seed` | The random seed. Defaults to variable `${system.seed}`. ~~int~~ | | `seed` | The random seed. Defaults to variable `${system.seed}`. ~~int~~ |
| `train_corpus` | Dot notation of the config location defining the train corpus. Defaults to `corpora.train`. ~~str~~ | | `train_corpus` | Dot notation of the config location defining the train corpus. Defaults to `corpora.train`. ~~str~~ |
@ -206,16 +206,16 @@ This section is optional and defines settings and controls for
used when you run [`spacy pretrain`](/api/cli#pretrain). used when you run [`spacy pretrain`](/api/cli#pretrain).
| Name | Description | | Name | Description |
| -------------- | ------------------------------------------------------------------------------------------------------ | | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `max_epochs` | Maximum number of epochs. Defaults to `1000`. ~~int~~ | | `max_epochs` | Maximum number of epochs. Defaults to `1000`. ~~int~~ |
| `dropout` | The dropout rate. Defaults to `0.2`. ~~float~~ | | `dropout` | The dropout rate. Defaults to `0.2`. ~~float~~ |
| `n_save_every` | Saving frequency. Defaults to `null`. ~~Optional[int]~~ | | `n_save_every` | Saving frequency. Defaults to `null`. ~~Optional[int]~~ |
| `objective` | The pretraining objective. Defaults to `{"type": "characters", "n_characters": 4}`. ~~Dict[str, Any]~~ | | `objective` | The pretraining objective. Defaults to `{"type": "characters", "n_characters": 4}`. ~~Dict[str, Any]~~ |
| `optimizer` | The optimizer. Defaults to [`Adam`](https://thinc.ai/docs/api-optimizers#adam). ~~Optimizer~~ | | `optimizer` | The optimizer. The learning rate schedule and other settings can be configured as part of the optimizer. Defaults to [`Adam`](https://thinc.ai/docs/api-optimizers#adam). ~~Optimizer~~ |
| `corpus` | Dot notation of the config location defining the train corpus. Defaults to `corpora.pretrain`. ~~str~~ | | `corpus` | Dot notation of the config location defining the corpus with raw text. Defaults to `corpora.pretrain`. ~~str~~ |
| `batcher` | Batcher for the training data. ~~Callable[[Iterator[Doc], Iterator[List[Doc]]]]~~ | | `batcher` | Callable that takes an iterator of [`Doc`](/api/doc) objects and yields batches of `Doc`s. Defaults to [`batch_by_words`](/api/top-level#batch_by_words). ~~Callable[[Iterator[Doc], Iterator[List[Doc]]]]~~ |
| `component` | Component to find the layer to pretrain. Defaults to `"tok2vec"`. ~~str~~ | | `component` | Component name to identify the layer with the model to pretrain. Defaults to `"tok2vec"`. ~~str~~ |
| `layer` | The layer to pretrain. If empty, the whole component model will be used. ~~str~~ | | `layer` | The specific layer of the model to pretrain. If empty, the whole model will be used. ~~str~~ |
### initialize {#config-initialize tag="section"} ### initialize {#config-initialize tag="section"}

2
website/docs/usage/training.md
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@ -378,7 +378,7 @@ weights and [resume training](/api/language#resume_training).
If you don't want a component to be updated, you can **freeze** it by adding it If you don't want a component to be updated, you can **freeze** it by adding it
to the `frozen_components` list in the `[training]` block. Frozen components are to the `frozen_components` list in the `[training]` block. Frozen components are
**not updated** during training and are included in the final trained pipeline **not updated** during training and are included in the final trained pipeline
as-is. as-is. They are also excluded when calling `nlp.initialize()`.
> #### Note on frozen components > #### Note on frozen components
> >