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Replace __class__ with __name__ in schema error message #14904

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merged 2 commits into from
Mar 10, 2025

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@harupy harupy commented Mar 7, 2025

Related Issues/PRs

Fix #14886

What changes are proposed in this pull request?

This code:

import numpy as np

import mlflow
from mlflow.models.signature import Schema
from mlflow.types.schema import ColSpec, TensorSpec

signature = mlflow.models.signature.ModelSignature(
    inputs=Schema(
        [ColSpec("float", "x"), TensorSpec(np.dtype("float64"), (-1, 28, 28), name="foo")],
    ),
)

throws this error:

mlflow.exceptions.MlflowException: Creating Schema with a combination of <class 'type'> and <class 'type'> is not supported. Please choose one of <class 'type'> or <class 'type'>

<class 'type'> or <class 'type'> should be ColSpec and TensorSpec.

How is this PR tested?

  • Existing unit/integration tests
  • New unit/integration tests
  • Manual tests

Does this PR require documentation update?

  • No. You can skip the rest of this section.
  • Yes. I've updated:
    • Examples
    • API references
    • Instructions

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.

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/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
  • 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/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/breaking-change - The PR will be mentioned in the "Breaking Changes" 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

Should this PR be included in the next patch release?

Yes should be selected for bug fixes, documentation updates, and other small changes. No should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.

What is a minor/patch release?
  • Minor release: a release that increments the second part of the version number (e.g., 1.2.0 -> 1.3.0).
    Bug fixes, doc updates and new features usually go into minor releases.
  • Patch release: a release that increments the third part of the version number (e.g., 1.2.0 -> 1.2.1).
    Bug fixes and doc updates usually go into patch releases.
  • Yes (this PR will be cherry-picked and included in the next patch release)
  • No (this PR will be included in the next minor release)

Signed-off-by: harupy <[email protected]>
@harupy harupy requested a review from Copilot March 7, 2025 07:06
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PR Overview

This pull request updates the exception message in the schema initialization to use the type names rather than their class objects.

  • Replaces ColSpec.class and TensorSpec.class with ColSpec.name and TensorSpec.name in the error message.
  • Enhances the clarity of the error message when an unsupported combination of types is provided.

Reviewed Changes

File Description
mlflow/types/schema.py Updates error message to display the class name string.

Copilot reviewed 1 out of 1 changed files in this pull request and generated no comments.

@github-actions github-actions bot added the rn/none List under Small Changes in Changelogs. label Mar 7, 2025
@harupy harupy changed the title Replace ColSpec.__class__ with ColSpec.__name__ in schema Replace __class__ with __name__ in schema error message Mar 7, 2025
@harupy harupy requested a review from mlflow-automation March 7, 2025 07:08
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@serena-ruan serena-ruan left a comment

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LGTM!

Signed-off-by: harupy <[email protected]>
@harupy harupy enabled auto-merge March 10, 2025 07:44
@harupy harupy added this pull request to the merge queue Mar 10, 2025
Merged via the queue into mlflow:master with commit 27ca473 Mar 10, 2025
41 checks passed
@harupy harupy deleted the fix-issue-14886 branch March 10, 2025 08:39
@harupy harupy added the v2.21.0 label Mar 14, 2025
TomeHirata pushed a commit to TomeHirata/mlflow that referenced this pull request Mar 14, 2025
TomeHirata pushed a commit that referenced this pull request Mar 14, 2025
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Clarify error message for mixing ColSpec and TensorSpec in Schema
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