Zgml
F 50 completed
Other
unknown / zig · small
56
Files
14,588
LOC
0
Frameworks
4
Languages
Pipeline State
completedRun ID
#1241088Phase
doneProgress
0%Started
2026-04-15 19:38:01Finished
2026-04-15 19:38:01LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
35.00Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #49193
Member of a group with 43 similar repo(s) — canonical #1591863 view group →
Repobility · MCP-ready · https://repobility.com
AI Prompt
Create a tensor library for machine learning using Zig. The library needs to support automatic differentiation, comptime shape checking, and auto-fused kernels. Key features to implement include a small primitive IR, a zero-noise API where tensors manage their own allocators, and compile-time shape tracking using a `Shaped` wrapper. The system should allow for graph building, including a `fusionPass()` for optimizing chains of elementwise operations, and should include modules for common loss functions and model architectures like linear and transformer blocks.
zig machine-learning tensor automatic-differentiation compilation-time
Generated by gemma4:latest
Catalog Information
Create a tensor library for machine learning using Zig. The library needs to support automatic differentiation, comptime shape checking, and auto-fused kernels. Key features to implement include a small primitive IR, a zero-noise API where tensors manage their own allocators, and compile-time shape tracking using a Shaped wrapper. The system should allow for graph building, including a fusionPass() for optimizing chains of elementwise operations, and should include modules for common loss fu
Tags
zig machine-learning tensor automatic-differentiation compilation-time
Quality Score
F
49.5/100
Structure
44
Code Quality
52
Documentation
52
Testing
0
Practices
67
Security
100
Dependencies
70
Strengths
- Consistent naming conventions (snake_case)
- Good security practices — no major issues detected
- Properly licensed project
Weaknesses
- No tests found — high risk of regressions
- No CI/CD configuration — manual testing and deployment
- 2138 duplicate lines detected — consider DRY refactoring
- 5 'god files' with >500 LOC need decomposition
Recommendations
- Add a test suite — start with critical path integration tests
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Add a linter configuration to enforce code style consistency
Languages
Frameworks
None detected
Symbols
constant3
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BinComp Dependency Hardening
All packages →2 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.