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1f58841e65
- 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
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" |