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feat: add spacy.WandbLogger.v3 with optional run_name and entity parameters (#9202)
* feat: add `spacy.WandbLogger.v3` with optional `run_name` and `entity` parameters * update versioning in docs Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
This commit is contained in:
Jozef Harag
GitHub
parent
1d57d78758
commit
865cfbc903
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@ -177,3 +177,87 @@ def wandb_logger(
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return log_step, finalize
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return setup_logger
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@registry.loggers("spacy.WandbLogger.v3")
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def wandb_logger(
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project_name: str,
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remove_config_values: List[str] = [],
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model_log_interval: Optional[int] = None,
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log_dataset_dir: Optional[str] = None,
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entity: Optional[str] = None,
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run_name: Optional[str] = None,
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):
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try:
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import wandb
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# test that these are available
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from wandb import init, log, join # noqa: F401
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except ImportError:
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raise ImportError(Errors.E880)
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console = console_logger(progress_bar=False)
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def setup_logger(
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nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
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) -> Tuple[Callable[[Dict[str, Any]], None], Callable[[], None]]:
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config = nlp.config.interpolate()
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config_dot = util.dict_to_dot(config)
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for field in remove_config_values:
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del config_dot[field]
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config = util.dot_to_dict(config_dot)
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run = wandb.init(project=project_name, config=config, entity=entity, reinit=True)
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if run_name:
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wandb.run.name = run_name
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console_log_step, console_finalize = console(nlp, stdout, stderr)
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def log_dir_artifact(
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path: str,
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name: str,
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type: str,
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metadata: Optional[Dict[str, Any]] = {},
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aliases: Optional[List[str]] = [],
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):
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dataset_artifact = wandb.Artifact(name, type=type, metadata=metadata)
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dataset_artifact.add_dir(path, name=name)
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wandb.log_artifact(dataset_artifact, aliases=aliases)
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if log_dataset_dir:
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log_dir_artifact(path=log_dataset_dir, name="dataset", type="dataset")
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def log_step(info: Optional[Dict[str, Any]]):
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console_log_step(info)
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if info is not None:
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score = info["score"]
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other_scores = info["other_scores"]
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losses = info["losses"]
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wandb.log({"score": score})
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if losses:
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wandb.log({f"loss_{k}": v for k, v in losses.items()})
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if isinstance(other_scores, dict):
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wandb.log(other_scores)
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if model_log_interval and info.get("output_path"):
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if info["step"] % model_log_interval == 0 and info["step"] != 0:
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log_dir_artifact(
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path=info["output_path"],
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name="pipeline_" + run.id,
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type="checkpoint",
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metadata=info,
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aliases=[
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f"epoch {info['epoch']} step {info['step']}",
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"latest",
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"best"
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if info["score"] == max(info["checkpoints"])[0]
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else "",
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],
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)
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def finalize() -> None:
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console_finalize()
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wandb.join()
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return log_step, finalize
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return setup_logger
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@ -462,7 +462,7 @@ start decreasing across epochs.
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</Accordion>
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#### spacy.WandbLogger.v2 {#WandbLogger tag="registered function"}
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#### spacy.WandbLogger.v3 {#WandbLogger tag="registered function"}
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> #### Installation
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>
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@ -494,19 +494,21 @@ remain in the config file stored on your local system.
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>
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> ```ini
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> [training.logger]
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> @loggers = "spacy.WandbLogger.v2"
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> @loggers = "spacy.WandbLogger.v3"
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> project_name = "monitor_spacy_training"
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> remove_config_values = ["paths.train", "paths.dev", "corpora.train.path", "corpora.dev.path"]
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> log_dataset_dir = "corpus"
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> model_log_interval = 1000
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> ```
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| Name | Description |
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| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
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| `project_name` | The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. ~~str~~ |
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| `remove_config_values` | A list of values to include from the config before it is uploaded to W&B (default: empty). ~~List[str]~~ |
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| `model_log_interval` | Steps to wait between logging model checkpoints to W&B dasboard (default: None). ~~Optional[int]~~ |
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| `log_dataset_dir` | Directory containing dataset to be logged and versioned as W&B artifact (default: None). ~~Optional[str]~~ |
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| Name | Description |
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| ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `project_name` | The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. ~~str~~ |
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| `remove_config_values` | A list of values to include from the config before it is uploaded to W&B (default: empty). ~~List[str]~~ |
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| `model_log_interval` | Steps to wait between logging model checkpoints to W&B dasboard (default: None). ~~Optional[int]~~ |
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| `log_dataset_dir` | Directory containing dataset to be logged and versioned as W&B artifact (default: None). ~~Optional[str]~~ |
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| `run_name` | The name of the run. If you don't specify a run_name, the name will be created by wandb library. (default: None ). ~~Optional[str]~~ |
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| `entity` | An entity is a username or team name where you're sending runs. If you don't specify an entity, the run will be sent to your default entity, which is usually your username. (default: None). ~~Optional[str]~~ |
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<Project id="integrations/wandb">
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