Add info-level logs when new fluent runs are during autologging #3874
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: Corey Zumar <corey.zumar@databricks.com>
dbczumar
commented
Dec 19, 2020
mlflow/tensorflow.py
Outdated
Comment on lines
887
to
909
| auto_end = False | ||
| if not mlflow.active_run(): | ||
| global _AUTOLOG_RUN_ID | ||
| if _AUTOLOG_RUN_ID: | ||
| try_mlflow_log(mlflow.start_run, _AUTOLOG_RUN_ID) | ||
| else: | ||
| try_mlflow_log(mlflow.start_run) | ||
| try_mlflow_log(mlflow.set_tag, MLFLOW_AUTOLOGGING, FLAVOR_NAME) | ||
| auto_end = True | ||
|
|
||
| serialized = original(self, *args, **kwargs) | ||
| try_mlflow_log( | ||
| log_model, | ||
| tf_saved_model_dir=serialized.decode("utf-8"), | ||
| tf_meta_graph_tags=[tag_constants.SERVING], | ||
| tf_signature_def_key="predict", | ||
| artifact_path="model", | ||
| ) | ||
| if ( | ||
| mlflow.active_run() is not None and mlflow.active_run().info.run_id == _AUTOLOG_RUN_ID | ||
| ) or auto_end: | ||
| try_mlflow_log(mlflow.end_run) | ||
| return serialized |
There was a problem hiding this comment.
This is an exact duplicate of the export_savedmodel body. We can apply the exact same patch code for export_saved_model and export_savedmodel using safe_patch without requiring duplicate code.
Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
github-actions
bot
added
area/tracking
Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
lorenzwalthert
pushed a commit
to lorenzwalthert/mlflow
that referenced
this pull request
Dec 23, 2020
…ow#3874) * Add info log Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Format Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Fix Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Print for user managed Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Black Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Rephrase slightly Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Patch Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
lorenzwalthert
pushed a commit
to lorenzwalthert/mlflow
that referenced
this pull request
Jan 15, 2021
…ow#3874) * Add info log Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Format Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Fix Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Print for user managed Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Black Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Rephrase slightly Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Patch Signed-off-by: Corey Zumar <corey.zumar@databricks.com>
harupy
pushed a commit
to chauhang/mlflow
that referenced
this pull request
Apr 8, 2021
…ow#3874) * Add info log Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Format Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Fix Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Print for user managed Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Black Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Rephrase slightly Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Patch Signed-off-by: Corey Zumar <corey.zumar@databricks.com> Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
harupy
pushed a commit
to wamartin-aml/mlflow
that referenced
this pull request
Jun 7, 2021
…ow#3874) * Add info log Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Format Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Fix Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Print for user managed Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Black Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Rephrase slightly Signed-off-by: Corey Zumar <corey.zumar@databricks.com> * Patch Signed-off-by: Corey Zumar <corey.zumar@databricks.com> Signed-off-by: harupy <17039389+harupy@users.noreply.github.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.
What changes are proposed in this pull request?
Adds some additional info logging to indicate when MLflow runs are created as a result of autologging workflows.
How is this patch tested?
Existing unit / integration tests for continued correctness
Release Notes
Added new info logs for MLflow run creation during autologging workflows.
Is this a user-facing change?
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/projects: MLproject format, project running backendsarea/scoring: Local serving, model deployment tools, spark UDFsarea/server-infra: MLflow server, JavaScript dev serverarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, JavaScript, plottingarea/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