NVIDIA / NVIDIA/TensorRT-LLM

[bug][AutoDeploy]: Phi-4 path fails with a shape mismatch error

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AutoDeploy bug
Dominant language
Python
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Merged PRs (30d)
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Description

System Info
  • CPU architecture: x86_64
  • GPU properties: not captured from CI artifact
  • Libraries
    • TensorRT-LLM branch or tag: main (pipeline context)
    • Container used: AutoDeploy CI container
  • OS: CI environment
Who can help?

No response

Information
  • The official example scripts
  • My own modified scripts
Tasks
  • An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
  • My own task or dataset (give details below)
Reproduction

Affected registry entries currently disabled in examples/auto_deploy/model_registry/models.yaml:

  • microsoft/phi-4
  • microsoft/Phi-4-reasoning
  • microsoft/Phi-4-reasoning-plus

All three fail in the AutoDeploy path with the same runtime shape-mismatch error.

Representative failure:

RuntimeError: a and b must have same reduction dim, but got [s44*s70, 5120] X [2560, 5120].

This looks like one shared Phi-4 family issue rather than three separate model-specific problems.

Expected behavior

Phi-4 entries should build a valid AutoDeploy graph and run without runtime shape mismatches.

actual behavior

The Phi-4 entries fail in AutoDeploy with a runtime shape-mismatch error before successful execution.

additional notes

NA

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Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the disabled entries in examples/auto_deploy/model_registry/models.yaml and reproduce the failure for microsoft/phi-4 or one of the related Phi-4 entries in the AutoDeploy CI container. Trace the reported reduction-dimension mismatch through the AutoDeploy path. Done means all three Phi-4 registry entries build a valid graph and execute without the runtime shape-mismatch error.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
ai, backend
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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