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https://github.com/MLSysBook/TinyTorch.git
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d82c75f9dc
✅ Rename all module directories: 00_setup → 01_setup, etc. ✅ Update convert_modules.py mappings for new directory names ✅ Update _toc.yml file paths and titles (1-14 instead of 0-13) ✅ Regenerate all overview pages with new numbering ✅ Fix all broken references in usage-paths and intro ✅ Update chapter references to use natural numbering Benefits: - More intuitive course progression starting from 1 - Matches academic course numbering conventions - Eliminates confusion about 'Module 0' concept - Cleaner mental model for students and instructors - All references and links properly updated Complete transformation: 14 modules now numbered 01-14
39 lines
1.1 KiB
YAML
39 lines
1.1 KiB
YAML
# TinyTorch Module Metadata
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# Essential system information for CLI tools and build systems
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name: "11_kernels"
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title: "Kernels - Hardware-Aware Optimization"
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description: "Custom operations, performance optimization, and hardware-aware computing for ML systems"
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# Dependencies - Used by CLI for module ordering and prerequisites
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dependencies:
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prerequisites: [
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"00_setup", "01_tensor", "02_activations", "03_layers",
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"04_networks", "05_cnn", "06_dataloader", "07_autograd",
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"08_optimizers", "09_training", "10_compression"
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]
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enables: ["12_benchmarking", "13_mlops"]
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# Package Export - What gets built into tinytorch package
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exports_to: "tinytorch.core.kernels"
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# File Structure - What files exist in this module
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files:
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dev_file: "kernels_dev.py"
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readme: "README.md"
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tests: "inline"
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# Components - What's implemented in this module
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components:
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- "matmul_custom"
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- "relu_custom"
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- "conv2d_custom"
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- "matmul_vectorized"
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- "matmul_cache_optimized"
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- "matmul_parallel"
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- "quantized_matmul"
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- "sparse_matmul"
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- "pruned_conv2d"
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- "KernelProfiler"
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- "PerformanceBenchmark"
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- "HardwareProfiler" |