Adds GitHub issue templates and PR template #97
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Establishes standardized templates for bug reports, feature requests, and performance issues to improve issue quality and streamline contributor workflow. Includes comprehensive sections for environment information, reproduction steps, and benchmarking details specific to Flash-DMA's CUDA-accelerated attention implementation.
LoserCheems
requested review from
Evanwu1125,
SNHuan,
Copilot and
wubingheng111
and removed request for
Copilot
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Pull Request Overview
This PR establishes standardized GitHub templates for issue reporting and pull requests to improve contributor workflow and issue quality for the Flash-DMA project. The templates are specifically tailored for a CUDA-accelerated attention implementation with sections for hardware configuration, performance benchmarking, and GPU-specific testing requirements.
- Adds comprehensive PR template with CUDA-specific checklist items and performance impact sections
- Creates three issue templates covering bug reports, feature requests, and performance issues
- Includes detailed environment information collection and benchmarking guidelines
Reviewed Changes
Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
.github/pull_request_template.md |
Comprehensive PR template with CUDA-specific sections, performance benchmarking, and detailed checklists |
.github/ISSUE_TEMPLATE/performance_issue.md |
Performance issue template with GPU profiling and benchmarking sections |
.github/ISSUE_TEMPLATE/feature_request.md |
Feature request template focusing on CUDA implementation details and use cases |
.github/ISSUE_TEMPLATE/bug_report.md |
Bug report template with environment detection and CUDA-specific context |
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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Establishes standardized templates for bug reports, feature requests, and performance issues to improve issue quality and streamline contributor workflow.
Includes comprehensive sections for environment information, reproduction steps, and benchmarking details specific to Flash-DMA's CUDA-accelerated attention implementation.