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Add support for audio classification pipelines to transformers #8492

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BenWilson2
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#xxx

What changes are proposed in this pull request?

Add support for audio classification pipelines to the transformers flavor.

How is this patch tested?

  • Existing unit/integration tests
  • New unit/integration tests
  • Manual tests (describe details, including test results, below)

Does this PR change the documentation?

  • No. You can skip the rest of this section.
  • Yes. Make sure the changed pages / sections render correctly in the documentation preview.

Release Notes

Is this a user-facing change?

  • No. You can skip the rest of this section.
  • Yes. Give a description of this change to be included in the release notes for MLflow users.

Add support for audio classification pipelines in the transformers flavor

What component(s), interfaces, languages, and integrations does this PR affect?

Components

  • area/artifacts: Artifact stores and artifact logging
  • area/build: Build and test infrastructure for MLflow
  • area/docs: MLflow documentation pages
  • area/examples: Example code
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
  • area/projects: MLproject format, project running backends
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/server-infra: MLflow Tracking server backend
  • area/tracking: Tracking Service, tracking client APIs, autologging

Interface

  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  • area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
  • area/windows: Windows support

Language

  • language/r: R APIs and clients
  • language/java: Java APIs and clients
  • language/new: Proposals for new client languages

Integrations

  • integrations/azure: Azure and Azure ML integrations
  • integrations/sagemaker: SageMaker integrations
  • integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

  • rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
  • rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
  • rn/feature - A new user-facing feature worth mentioning in the release notes
  • rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
  • rn/documentation - A user-facing documentation change worth mentioning in the release notes

Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
@github-actions github-actions bot added area/models MLmodel format, model serialization/deserialization, flavors rn/feature Mention under Features in Changelogs. labels May 22, 2023
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Documentation preview for 13f34a2 will be available here when this CircleCI job completes successfully.

More info

@BenWilson2 BenWilson2 requested a review from dbczumar May 22, 2023 20:23
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@harupy harupy left a comment

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LGTM!

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@WeichenXu123 WeichenXu123 left a comment

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LGTM

@BenWilson2 BenWilson2 merged commit 7796af2 into mlflow:master May 23, 2023
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@BenWilson2 BenWilson2 deleted the transformers-audio-classification branch May 23, 2023 13:01
BenWilson2 added a commit to BenWilson2/mlflow that referenced this pull request May 23, 2023
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
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4 participants