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W&B integration: Optional support for dataset and model checkpoint logging and versioning (#7429)
* Add optional artifacts logging * Update docs * Update spacy/training/loggers.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/training/loggers.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/training/loggers.py Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Bump WandbLogger Version * Add documentation of v1 to legacy docs * bump spacy-legacy to 3.0.2 (to be released) Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
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Ayush Chaurasia
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.github/contributors/AyushExel.md
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# spaCy contributor agreement
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This spaCy Contributor Agreement (**"SCA"**) is based on the
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[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
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The SCA applies to any contribution that you make to any product or project
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managed by us (the **"project"**), and sets out the intellectual property rights
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you grant to us in the contributed materials. The term **"us"** shall mean
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[ExplosionAI GmbH](https://explosion.ai/legal). The term
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**"you"** shall mean the person or entity identified below.
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If you agree to be bound by these terms, fill in the information requested
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below and include the filled-in version with your first pull request, under the
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folder [`.github/contributors/`](/.github/contributors/). The name of the file
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should be your GitHub username, with the extension `.md`. For example, the user
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example_user would create the file `.github/contributors/example_user.md`.
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Read this agreement carefully before signing. These terms and conditions
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constitute a binding legal agreement.
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## Contributor Agreement
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1. The term "contribution" or "contributed materials" means any source code,
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object code, patch, tool, sample, graphic, specification, manual,
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documentation, or any other material posted or submitted by you to the project.
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2. With respect to any worldwide copyrights, or copyright applications and
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registrations, in your contribution:
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* you hereby assign to us joint ownership, and to the extent that such
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assignment is or becomes invalid, ineffective or unenforceable, you hereby
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grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
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royalty-free, unrestricted license to exercise all rights under those
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copyrights. This includes, at our option, the right to sublicense these same
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rights to third parties through multiple levels of sublicensees or other
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licensing arrangements;
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* you agree that each of us can do all things in relation to your
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contribution as if each of us were the sole owners, and if one of us makes
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a derivative work of your contribution, the one who makes the derivative
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work (or has it made will be the sole owner of that derivative work;
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* you agree that you will not assert any moral rights in your contribution
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against us, our licensees or transferees;
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* you agree that we may register a copyright in your contribution and
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exercise all ownership rights associated with it; and
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* you agree that neither of us has any duty to consult with, obtain the
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consent of, pay or render an accounting to the other for any use or
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distribution of your contribution.
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3. With respect to any patents you own, or that you can license without payment
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to any third party, you hereby grant to us a perpetual, irrevocable,
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non-exclusive, worldwide, no-charge, royalty-free license to:
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* make, have made, use, sell, offer to sell, import, and otherwise transfer
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your contribution in whole or in part, alone or in combination with or
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included in any product, work or materials arising out of the project to
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which your contribution was submitted, and
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* at our option, to sublicense these same rights to third parties through
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multiple levels of sublicensees or other licensing arrangements.
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4. Except as set out above, you keep all right, title, and interest in your
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contribution. The rights that you grant to us under these terms are effective
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on the date you first submitted a contribution to us, even if your submission
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took place before the date you sign these terms.
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5. You covenant, represent, warrant and agree that:
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* Each contribution that you submit is and shall be an original work of
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authorship and you can legally grant the rights set out in this SCA;
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* to the best of your knowledge, each contribution will not violate any
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third party's copyrights, trademarks, patents, or other intellectual
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property rights; and
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* each contribution shall be in compliance with U.S. export control laws and
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other applicable export and import laws. You agree to notify us if you
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become aware of any circumstance which would make any of the foregoing
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representations inaccurate in any respect. We may publicly disclose your
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participation in the project, including the fact that you have signed the SCA.
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6. This SCA is governed by the laws of the State of California and applicable
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U.S. Federal law. Any choice of law rules will not apply.
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7. Please place an “x” on one of the applicable statement below. Please do NOT
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mark both statements:
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* [X] I am signing on behalf of myself as an individual and no other person
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or entity, including my employer, has or will have rights with respect to my
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contributions.
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* [ ] I am signing on behalf of my employer or a legal entity and I have the
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actual authority to contractually bind that entity.
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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | Ayush Chaurasia |
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| Company name (if applicable) | |
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| Title or role (if applicable) | |
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| Date | 2021-03-12 |
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| GitHub username | AyushExel |
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| Website (optional) | |
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@ -1,5 +1,5 @@
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# Our libraries
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spacy-legacy>=3.0.0,<3.1.0
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spacy-legacy>=3.0.2,<3.1.0
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cymem>=2.0.2,<2.1.0
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preshed>=3.0.2,<3.1.0
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thinc>=8.0.2,<8.1.0
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@ -37,7 +37,7 @@ setup_requires =
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thinc>=8.0.2,<8.1.0
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install_requires =
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# Our libraries
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spacy-legacy>=3.0.0,<3.1.0
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spacy-legacy>=3.0.2,<3.1.0
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murmurhash>=0.28.0,<1.1.0
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cymem>=2.0.2,<2.1.0
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preshed>=3.0.2,<3.1.0
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@ -101,8 +101,13 @@ def console_logger(progress_bar: bool = False):
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return setup_printer
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@registry.loggers("spacy.WandbLogger.v1")
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def wandb_logger(project_name: str, remove_config_values: List[str] = []):
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@registry.loggers("spacy.WandbLogger.v2")
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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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):
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try:
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import wandb
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from wandb import init, log, join # test that these are available
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@ -119,9 +124,23 @@ def wandb_logger(project_name: str, remove_config_values: List[str] = []):
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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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wandb.init(project=project_name, config=config, reinit=True)
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run = wandb.init(project=project_name, config=config, reinit=True)
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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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@ -133,6 +152,21 @@ def wandb_logger(project_name: str, remove_config_values: List[str] = []):
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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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@ -96,12 +96,13 @@ def train(
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log_step, finalize_logger = train_logger(nlp, stdout, stderr)
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try:
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for batch, info, is_best_checkpoint in training_step_iterator:
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log_step(info if is_best_checkpoint is not None else None)
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if is_best_checkpoint is not None:
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with nlp.select_pipes(disable=frozen_components):
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update_meta(T, nlp, info)
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if output_path is not None:
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save_checkpoint(is_best_checkpoint)
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info["output_path"] = str(output_path / DIR_MODEL_LAST)
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log_step(info if is_best_checkpoint is not None else None)
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except Exception as e:
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if output_path is not None:
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stdout.write(
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@ -140,4 +140,27 @@ network has an internal CNN Tok2Vec layer and uses attention.
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| `ngram_size` | Determines the maximum length of the n-grams in the BOW model. For instance, `ngram_size=3`would give unigram, trigram and bigram features. ~~int~~ |
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| `dropout` | The dropout rate. ~~float~~ |
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| `nO` | Output dimension, determined by the number of different labels. If not set, the [`TextCategorizer`](/api/textcategorizer) component will set it when `initialize` is called. ~~Optional[int]~~ |
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| **CREATES** | The model using the architecture. ~~Model[List[Doc], Floats2d]~~ |
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| **CREATES** | The model using the architecture. ~~Model[List[Doc], Floats2d]~~ |
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## Loggers {#loggers}
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These functions are available from `@spacy.registry.loggers`.
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### spacy.WandbLogger.v1 {#WandbLogger_v1}
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The first version of the [`WandbLogger`](/api/top-level#WandbLogger) did not yet
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support the `log_dataset_dir` and `model_log_interval` arguments.
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> #### Example config
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>
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> ```ini
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> [training.logger]
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> @loggers = "spacy.WandbLogger.v1"
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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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> ```
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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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@ -461,7 +461,7 @@ start decreasing across epochs.
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</Accordion>
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#### spacy.WandbLogger.v1 {#WandbLogger tag="registered function"}
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#### spacy.WandbLogger.v2 {#WandbLogger tag="registered function"}
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> #### Installation
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>
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@ -493,15 +493,19 @@ 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.v1"
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> @loggers = "spacy.WandbLogger.v2"
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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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<Project id="integrations/wandb">
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@ -995,7 +995,7 @@ your results.
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>
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> ```ini
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> [training.logger]
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> @loggers = "spacy.WandbLogger.v1"
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> @loggers = "spacy.WandbLogger.v2"
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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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> ```
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