mlcommons / mlcommons/inference

[Llama3] Docker dependencies issues

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Python
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Description

The following issues appear when running the LLM reference implementation

Dependencies in the docker container:

Collecting mistral-common>=1.4.4 (from mistral-common[opencv]>=1.4.4->vllm==0.6.3->-r requirements.txt (line 8))
  Downloading mistral_common-1.5.0-py3-none-any.whl.metadata (4.6 kB)
  Downloading mistral_common-1.4.4-py3-none-any.whl.metadata (4.6 kB)
ERROR: Cannot install -r requirements.txt (line 8), mistral-common and sentencepiece==0.1.99 because these package versions have conflicting dependencies.

The conflict is caused by:
    The user requested sentencepiece==0.1.99
    vllm 0.6.3 depends on sentencepiece
    mistral-common 1.5.1 depends on sentencepiece==0.2.0
    The user requested sentencepiece==0.1.99
    vllm 0.6.3 depends on sentencepiece
    mistral-common 1.5.0 depends on sentencepiece==0.2.0
    The user requested sentencepiece==0.1.99
    vllm 0.6.3 depends on sentencepiece
    mistral-common 1.4.4 depends on sentencepiece==0.2.0

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip to attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

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 by reproducing the dependency resolution failure in the Docker container and inspect requirements.txt, especially line 8 and the pinned sentencepiece version. Determine compatible dependency constraints so the Llama3 reference implementation installs successfully, then verify that the container builds without the pip ResolutionImpossible error.

Written by the indexing model from the issue text.

Assessment

Tech stack
docker, python
Domain
devops, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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