[BUG] difference in onnx score when using batch

[pranayVyas]

SynapseML version

0.11.4

System information

• Language version (e.g. python 3.8, scala 2.12): 3.10
• Spark Version (e.g. 3.2.3): 3.2.0
• Spark Platform (e.g. Synapse, Databricks): yarn

Describe the problem

Hello, I would like to inquire if anyone has faced similar issues where scores are different when batch size is 1 and batch size eis higher number say 5000.
The score is consistently same for each batch size. So not a model issue. Score with batch size 1 matches that when produced with onnx runtime with pandas dataframe.

Difference in score between these two are also significant.

Code to reproduce issue

Unfortunately will not be able to produce code.

Other info / logs

No response

What component(s) does this bug affect?

• area/cognitive: Cognitive project
• area/core: Core project
• area/deep-learning: DeepLearning project
• area/lightgbm: Lightgbm project
• area/opencv: Opencv project
• area/vw: VW project
• area/website: Website
• area/build: Project build system
• area/notebooks: Samples under notebooks folder
• area/docker: Docker usage
• area/models: models related issue

What language(s) does this bug affect?

• language/scala: Scala source code
• language/python: Pyspark APIs
• language/r: R APIs
• language/csharp: .NET APIs
• language/new: Proposals for new client languages

What integration(s) does this bug affect?

• integrations/synapse: Azure Synapse integrations
• integrations/azureml: Azure ML integrations
• integrations/databricks: Databricks integrations