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https://github.com/MLSysBook/TinyTorch.git
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869d4251e7
- Remove student-facing bloat (learning objectives, time estimates, pedagogical details) - Remove assessment sections (not needed for operational metadata) - Streamline to essential system information only: - Module identification and dependencies - Package export configuration - File structure and component listings - Updated existing files (6): setup, tensor, activations, layers, autograd, optimizers - Created missing files (3): networks, cnn, dataloader - Consistent 25-26 line format across all 9 modules Result: Pure operational metadata for CLI tools and build systems Perfect for instructor/staff development workflow
26 lines
737 B
YAML
26 lines
737 B
YAML
# TinyTorch Module Metadata
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# Essential system information for CLI tools and build systems
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name: "autograd"
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title: "Autograd"
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description: "Automatic differentiation engine for gradient computation"
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# Dependencies - Used by CLI for module ordering and prerequisites
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dependencies:
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prerequisites: ["setup", "tensor", "activations"]
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enables: ["optimizers", "training"]
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# Package Export - What gets built into tinytorch package
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exports_to: "tinytorch.core.autograd"
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# File Structure - What files exist in this module
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files:
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dev_file: "autograd_dev.py"
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test_file: "tests/test_autograd.py"
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readme: "README.md"
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# Components - What's implemented in this module
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components:
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- "Variable"
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- "backward"
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- "gradient_computation" |