Add sentence-transformers as a named flavor #8479
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
github-actions
bot
added
area/models
|
Documentation preview for ae418dd will be available here when this CircleCI job completes successfully. More info
|
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
mlflow/sentence_transformers.py
Outdated
| extra_pip_requirements: Optional[Union[List[str], str]] = None, | ||
| conda_env=None, | ||
| metadata: Dict[str, Any] = None, | ||
| **kwargs, |
There was a problem hiding this comment.
The **kwargs is not used, shall we remove this argument ?
There was a problem hiding this comment.
Thanks. I forgot to remove that during evaluating ser/deser behavior.
mlflow/sentence_transformers.py
Outdated
| :param model: A trained ``sentence-transformers`` model. | ||
| :param path: Local path destination for the serialized model to be saved. | ||
| :param inference_config: | ||
| A dict of valid overrides that can be applied to a ``sentence-transformer`` model instance |
There was a problem hiding this comment.
Suggested change
| A dict of valid overrides that can be applied to a ``sentence-transformer`` model instance | |
| A dict of valid inference configs that can be applied to a ``sentence-transformer`` model instance and override default inference configs |
|
|
||
| model.save(str(model_data_path)) | ||
|
|
||
| pyfunc.add_to_model( |
There was a problem hiding this comment.
We should also define def _load_pyfunc(path) for this flavor.
There was a problem hiding this comment.
We'll have a follow-on PR for pyfunc implementation
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
BenWilson2
added a commit
to BenWilson2/mlflow
that referenced
this pull request
May 23, 2023
* WIP Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> * Add basic serialization functionality for sentence-transformers Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> * fix docs linting Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> * fix lint and test Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> * remove useless kwargs entries Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> --------- Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Add basic serialization (save_model, load_model, log_model) and signature default assignment for the sentence-transformers package.
How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
Introduce a sentence-transformers flavor.
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes