Files
TinyTorch/modules/source/13_benchmarking/module.yaml
Vijay Janapa Reddi 4f9c6e40bd refactor: Implement YAML-based difficulty and time system
- Added educational metadata (difficulty, time_estimate) to all module.yaml files
- Updated convert_readmes.py to read from YAML instead of hardcoded mappings
- Standardized difficulty progression: 🥷
- Fixed path resolution for YAML reading in book build process
- Eliminated duplication: single source of truth for educational metadata
- Capstone gets special ninja treatment (🥷) as beyond-expert level
2025-07-16 11:48:09 -04:00

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1.1 KiB
YAML

# TinyTorch Module Metadata
# Essential system information for CLI tools and build systems
name: "12_benchmarking"
title: "Benchmarking - Systematic ML Performance Evaluation"
description: "Industry-standard benchmarking methodology for ML systems, inspired by MLPerf patterns"
# Dependencies - Used by CLI for module ordering and prerequisites
dependencies:
prerequisites: [
"00_setup", "01_tensor", "02_activations", "03_layers",
"04_networks", "05_cnn", "06_dataloader", "07_autograd",
"08_optimizers", "09_training", "10_compression", "11_kernels"
]
enables: ["13_mlops"]
# Package Export - What gets built into tinytorch package
exports_to: "tinytorch.core.benchmarking"
# File Structure - What files exist in this module
files:
dev_file: "benchmarking_dev.py"
readme: "README.md"
tests: "inline"
# Educational Metadata
difficulty: "⭐⭐⭐⭐"
time_estimate: "4-5 hours"
# Components - What's implemented in this module
components:
- "TinyTorchPerf"
- "BenchmarkScenarios"
- "StatisticalValidator"
- "ResultsAnalyzer"
- "PerformanceReporter"