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docs(module 19): add MLPerf trademark attribution and pedagogical framing

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- MLPerf® is a trademark of MLCommons
- This module teaches the principles of MLPerf-style benchmarking
This commit is contained in:
Vijay Janapa Reddi
2026-02-22 13:19:43 -05:00
parent 335bad8cd0
commit 68d446edcf
1 changed files with 7 additions and 1 deletions
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tinytorch/src/19_benchmarking/19_benchmarking.py
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@@ -2108,7 +2108,10 @@ if __name__ == "__main__":
"""
### MLPerf - Standardized Industry Benchmarking
MLPerf provides standardized benchmarks that enable fair comparison across different systems, similar to how MLPerf works for larger models. This is crucial for reproducible research and industry adoption.
MLPerf® is a trademark of MLCommons. This module provides MLPerf-style standardized
benchmarks that enable fair comparison across different systems, similar to how the
official MLPerf suite works for larger models. This is important for reproducible
research and industry adoption.
### Why Standardization Matters
@@ -2206,6 +2209,9 @@ class MLPerf:
"""
MLPerf-style standardized benchmarking for edge ML systems.
MLPerf® is a trademark of MLCommons. This module teaches the principles of
MLPerf-style benchmarking through a simplified suite inspired by MLPerf Tiny.
Provides fixed benchmark configurations with target thresholds,
standardized measurement protocols, and compliance reporting.