1 dépôt
Awesome GitHub RepositoriesHierarchical Parameter Optimizations
Traversing nested parameter structures to apply optimizers that support complex model architectures.
Distinct from Layer Parameter Optimization: Distinct from Layer Parameter Optimization: focuses on traversing nested structures for optimization, not reducing layer-level parameter count.
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Awesome Hierarchical Parameter Optimizations GitHub Repositories
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- tensorflow/swift
tensorflow/swift
6,131Voir sur GitHubSwift for TensorFlow is a custom toolchain that extends the Swift language with first-class automatic differentiation and differentiable types, enabling gradient-based computation directly within the compiler. It integrates the Swift compiler with TensorFlow runtime and XLA backends, allowing tensor operations to be compiled and executed on hardware-accelerated hardware for high-performance machine learning. The project distinguishes itself through compiler-integrated automatic differentiation that computes gradients of user-defined functions and types during compilation, eliminating the need
Traverses nested parameter structures to apply optimizers for complex model architectures.
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