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Merge pull request #6134 from explosion/feature/training_before_to_disk
This commit is contained in:
Ines Montani
GitHub
commit
74e1f192b4
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@ -97,6 +97,7 @@ def train(
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dev_corpus = dot_to_object(config, T_cfg["dev_corpus"])
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batcher = T_cfg["batcher"]
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train_logger = T_cfg["logger"]
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before_to_disk = create_before_to_disk_callback(T_cfg["before_to_disk"])
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# Components that shouldn't be updated during training
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frozen_components = T_cfg["frozen_components"]
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# Sourced components that require resume_training
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@ -167,6 +168,7 @@ def train(
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with nlp.select_pipes(disable=frozen_components):
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update_meta(T_cfg, nlp, info)
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with nlp.use_params(optimizer.averages):
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nlp = before_to_disk(nlp)
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nlp.to_disk(output_path / "model-best")
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progress = tqdm.tqdm(total=T_cfg["eval_frequency"], leave=False)
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progress.set_description(f"Epoch {info['epoch']}")
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@ -179,6 +181,7 @@ def train(
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f"Aborting and saving the final best model. "
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f"Encountered exception: {str(e)}"
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)
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nlp = before_to_disk(nlp)
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nlp.to_disk(output_path / "model-final")
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raise e
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finally:
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@ -233,6 +236,21 @@ def create_evaluation_callback(
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return evaluate
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def create_before_to_disk_callback(
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callback: Optional[Callable[[Language], Language]]
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) -> Callable[[Language], Language]:
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def before_to_disk(nlp: Language) -> Language:
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if not callback:
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return nlp
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modified_nlp = callback(nlp)
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if not isinstance(modified_nlp, Language):
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err = Errors.E914.format(name="before_to_disk", value=type(modified_nlp))
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raise ValueError(err)
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return modified_nlp
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return before_to_disk
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def train_while_improving(
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nlp: Language,
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optimizer: Optimizer,
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@ -72,6 +72,8 @@ frozen_components = []
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dev_corpus = "corpora.dev"
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# Location in the config where the train corpus is defined
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train_corpus = "corpora.train"
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# Optional callback before nlp object is saved to disk after training
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before_to_disk = null
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[training.logger]
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@loggers = "spacy.ConsoleLogger.v1"
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@ -480,6 +480,9 @@ class Errors:
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E201 = ("Span index out of range.")
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# TODO: fix numbering after merging develop into master
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E914 = ("Executing {name} callback failed. Expected the function to "
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"return the nlp object but got: {value}. Maybe you forgot to return "
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"the modified object in your function?")
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E915 = ("Can't use score '{name}' to calculate final weighted score. Expected "
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"float or int but got: {score_type}. To exclude the score from the "
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"final score, set its weight to null in the [training.score_weights] "
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@ -216,6 +216,7 @@ class ConfigSchemaTraining(BaseModel):
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optimizer: Optimizer = Field(..., title="The optimizer to use")
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logger: Logger = Field(..., title="The logger to track training progress")
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frozen_components: List[str] = Field(..., title="Pipeline components that shouldn't be updated during training")
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before_to_disk: Optional[Callable[["Language"], "Language"]] = Field(..., title="Optional callback to modify nlp object after training, before it's saved to disk")
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# fmt: on
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class Config:
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@ -180,26 +180,27 @@ single corpus once and then divide it up into `train` and `dev` partitions.
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This section defines settings and controls for the training and evaluation
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process that are used when you run [`spacy train`](/api/cli#train).
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| Name | Description |
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| --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `accumulate_gradient` | Whether to divide the batch up into substeps. Defaults to `1`. ~~int~~ |
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| `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]]]]~~ |
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| `dev_corpus` | Dot notation of the config location defining the dev corpus. Defaults to `corpora.dev`. ~~str~~ |
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| `dropout` | The dropout rate. Defaults to `0.1`. ~~float~~ |
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| `eval_frequency` | How often to evaluate during training (steps). Defaults to `200`. ~~int~~ |
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| `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]~~ |
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| `gpu_allocator` | Library for cupy to route GPU memory allocation to. Can be `"pytorch"` or `"tensorflow"`. Defaults to variable `${system.gpu_allocator}`. ~~str~~ |
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| `init_tok2vec` | Optional path to pretrained tok2vec weights created with [`spacy pretrain`](/api/cli#pretrain). Defaults to variable `${paths.init_tok2vec}`. ~~Optional[str]~~ |
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| `lookups` | Additional lexeme and vocab data from [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data). Defaults to `null`. ~~Optional[Lookups]~~ |
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| `max_epochs` | Maximum number of epochs to train for. Defaults to `0`. ~~int~~ |
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| `max_steps` | Maximum number of update steps to train for. Defaults to `20000`. ~~int~~ |
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| `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~~ |
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| `patience` | How many steps to continue without improvement in evaluation score. Defaults to `1600`. ~~int~~ |
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| `raw_text` | Optional path to a jsonl file with unlabelled text documents for a [rehearsal](/api/language#rehearse) step. Defaults to variable `${paths.raw}`. ~~Optional[str]~~ |
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| `score_weights` | Score names shown in metrics mapped to their weight towards the final weighted score. See [here](/usage/training#metrics) for details. Defaults to `{}`. ~~Dict[str, float]~~ |
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| `seed` | The random seed. Defaults to variable `${system.seed}`. ~~int~~ |
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| `train_corpus` | Dot notation of the config location defining the train corpus. Defaults to `corpora.train`. ~~str~~ |
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| `vectors` | Name or path of pipeline containing pretrained word vectors to use, e.g. created with [`init vocab`](/api/cli#init-vocab). Defaults to `null`. ~~Optional[str]~~ |
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| Name | Description |
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| --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `accumulate_gradient` | Whether to divide the batch up into substeps. Defaults to `1`. ~~int~~ |
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| `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]]]]~~ |
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| `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]]~~ |
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| `dev_corpus` | Dot notation of the config location defining the dev corpus. Defaults to `corpora.dev`. ~~str~~ |
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| `dropout` | The dropout rate. Defaults to `0.1`. ~~float~~ |
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| `eval_frequency` | How often to evaluate during training (steps). Defaults to `200`. ~~int~~ |
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| `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]~~ |
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| `gpu_allocator` | Library for cupy to route GPU memory allocation to. Can be `"pytorch"` or `"tensorflow"`. Defaults to variable `${system.gpu_allocator}`. ~~str~~ |
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| `init_tok2vec` | Optional path to pretrained tok2vec weights created with [`spacy pretrain`](/api/cli#pretrain). Defaults to variable `${paths.init_tok2vec}`. ~~Optional[str]~~ |
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| `lookups` | Additional lexeme and vocab data from [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data). Defaults to `null`. ~~Optional[Lookups]~~ |
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| `max_epochs` | Maximum number of epochs to train for. Defaults to `0`. ~~int~~ |
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| `max_steps` | Maximum number of update steps to train for. Defaults to `20000`. ~~int~~ |
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| `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~~ |
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| `patience` | How many steps to continue without improvement in evaluation score. Defaults to `1600`. ~~int~~ |
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| `raw_text` | Optional path to a jsonl file with unlabelled text documents for a [rehearsal](/api/language#rehearse) step. Defaults to variable `${paths.raw}`. ~~Optional[str]~~ |
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| `score_weights` | Score names shown in metrics mapped to their weight towards the final weighted score. See [here](/usage/training#metrics) for details. Defaults to `{}`. ~~Dict[str, float]~~ |
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| `seed` | The random seed. Defaults to variable `${system.seed}`. ~~int~~ |
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| `train_corpus` | Dot notation of the config location defining the train corpus. Defaults to `corpora.train`. ~~str~~ |
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| `vectors` | Name or path of pipeline containing pretrained word vectors to use, e.g. created with [`init vocab`](/api/cli#init-vocab). Defaults to `null`. ~~Optional[str]~~ |
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### pretraining {#config-pretraining tag="section,optional"}
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