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WalkthroughA conditional installation step for the Changes
Sequence Diagram(s)sequenceDiagram
participant BuildProcess
participant Dockerfile
participant pip
BuildProcess->>Dockerfile: Build with PYTORCH_VERSION and CUDA args
alt PYTORCH_VERSION==2.6.0 and CUDA==124
Dockerfile->>pip: Install flash-attn==2.8.0.post2 (force build from source)
else Other versions
Dockerfile-->>pip: Skip flash-attn install
end
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Actionable comments posted: 1
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docker/Dockerfile-base(1 hunks)
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🧠 Learnings (2)
📓 Common learnings
Learnt from: NanoCode012
PR: axolotl-ai-cloud/axolotl#2854
File: README.md:73-77
Timestamp: 2025-07-02T02:56:20.788Z
Learning: For Axolotl Docker commands, the `--ipc=host` flag should be included by default to prevent shared memory failures that commonly occur with PyTorch DataLoaders and multiprocessing during machine learning training workflows.
docker/Dockerfile-base (1)
Learnt from: NanoCode012
PR: axolotl-ai-cloud/axolotl#2854
File: README.md:73-77
Timestamp: 2025-07-02T02:56:20.788Z
Learning: For Axolotl Docker commands, the `--ipc=host` flag should be included by default to prevent shared memory failures that commonly occur with PyTorch DataLoaders and multiprocessing during machine learning training workflows.
🔇 Additional comments (1)
docker/Dockerfile-base (1)
41-43: Implementation looks technically sound.The conditional installation logic is well-implemented:
- Proper bash conditional syntax with string comparison
- Inline environment variable setting for forcing source build
- Appropriate package version pinning
- Good placement in the Dockerfile after core dependencies
Codecov ReportAll modified and coverable lines are covered by tests ✅ 📢 Thoughts on this report? Let us know! |
winglian
removed
the
scheduled_release
1 participant
fa2 builds are broken when using torch 2.6.0 + cu124. let's build it from source on these base images
Summary by CodeRabbit