A Toolkit to Help Optimize Onnx Model
C-Rank Grade: B (Solid) - 51/100
External PR Merge Rate: 85%
Response Time: <1h
First Timer Success: -
inisis/OnnxSlim has a recorded first-timer success rate of 0.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in inisis/OnnxSlim respond to incoming external pull requests in approximately 0.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 51.0 places inisis/OnnxSlim in the B tier.
The external contributor pull request merge rate for inisis/OnnxSlim is 84.6%, based on public PR activity from non-core contributors.
inisis/OnnxSlim currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Highly welcoming maintainers in inisis/OnnxSlim. Prompt code reviews with positive guidance for new contributors.
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Historical health & responsiveness evolution
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Maintainers are most responsive around 16:00 UTC (16:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 14:00 to 18:00 UTC (14:00 - 18:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (96% approval). Large PRs (>500 lines) take ~1 hours (38% approval). Keep your diff compact for rapid review.
Description The current symbolic shape inference in ONNX covers only a subset of operators. This limitation affects models with dynamic or partially known shapes, where accurate shape propagation is critical for graph optimization and validation. This issue aims to extend symbolic shape inference support to more ONNX operators, improving the overall robustness of shape inference in dynamic scenarios. Motivation Improve handling of dynamic and symbolic dimensions Enable better optimization passes and graph transformations Reduce reliance on runtime shape inference Improve compatibility with exported models from frameworks like PyTorch and TensorFlow Background onnxslim provides a symbolic shape inference utility (e.g., symbolic_shape_infer.py) that propagates shape information using symbolic dimensions. However, many operators either: Fall back to unknown shapes, or Only support static shape inference Expanding support will help downstream tools (e.g., compilers, runtimes) make bett
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When evaluating whether to contribute to inisis/OnnxSlim, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of inisis/OnnxSlim acknowledge new external contributions in approximately <1 hour. Out of all submitted pull requests from non-core authors in the last 180-day window, 84.6% were successfully merged into the primary branch.
inisis/OnnxSlim has a recorded first-timer success rate of 0.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~<1 hour. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 51.0 places inisis/OnnxSlim in the Solid tier.
The external pull request merge rate is 84.6%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, inisis/OnnxSlim currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for inisis/OnnxSlim are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.