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Systems for allocating, tracking, and reclaiming memory used by large multidimensional arrays during computation.
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This repository provides a collection of practical demonstrations and implementation guides for machine learning tasks using TensorFlow.js. It serves as a resource for developers to explore model architectures, training workflows, and data manipulation techniques across domains such as computer vision, natural language
Automated cleanup scopes and manual disposal utilities provide granular control over tensor lifecycles, which is essential for stable GPU-based execution.