Files
TinyTorch/modules/source/13_mlops/module.yaml
Vijay Janapa Reddi 1f58841e65 Clean up module configurations and add kernels integration tests
- Standardize module.yaml files (11-13) to match concise format of early modules
- Remove verbose sections, keep essential metadata only
- Update kernels README to match TinyTorch module style standards
- Add comprehensive integration tests for kernels module
- Test hardware-optimized operations with real TinyTorch components
- Prepare for systematic integration testing across all modules
2025-07-14 19:12:20 -04:00

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YAML

# TinyTorch Module Metadata
# Essential system information for CLI tools and build systems
name: "13_mlops"
title: "MLOps - Production ML Systems"
description: "Complete MLOps pipeline for production deployment, monitoring, and continuous learning"
# 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",
"12_benchmarking"
]
enables: []
# Package Export - What gets built into tinytorch package
exports_to: "tinytorch.core.mlops"
# File Structure - What files exist in this module
files:
dev_file: "mlops_dev.py"
readme: "README.md"
tests: "inline"
# Components - What's implemented in this module
components:
- "ModelMonitor"
- "DriftDetector"
- "RetrainingTrigger"
- "MLOpsPipeline"