{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Provides an ahead-of-time compiled module for faster DLPack v1.2 conversion with torch, avoiding JIT compilation overhead and compiler toolchain requirements.","skillfed_tags":["dlpack-interop","torch-extension","performance-optimization"],"use_cases":["Speed up initialization of torch-based applications that use DLPack-compatible libraries.","Deploy torch models in environments where a C++ compiler toolchain is unavailable or undesirable.","Reduce startup latency in serverless or containerized torch inference pipelines.","Avoid JIT compilation failures in restricted or minimal Python environments."],"what_it_does":"torch-c-dlpack-ext is a compiled extension that accelerates DLPack tensor conversion for torch by providing an ahead-of-time compiled implementation of DLPack v1.2 support. By default, torch-dependent tools will JIT-compile this functionality on first load, which adds startup overhead and requires a compiler toolchain in the user environment. Installing this wheel lets you skip that JIT step entirely and use a pre-compiled version instead.\n\nThe package is narrowly scoped: it exists solely to optimize one specific operation (DLPack conversion) and avoid the friction of runtime compilation. It has no public API of its own\u2014it works by providing a faster implementation that downstream libraries can detect and use automatically. If your workflow involves torch and libraries that use DLPack, this can reduce initialization time and eliminate compiler dependencies.","worth_installing":"Yes, if you use torch with DLPack-dependent libraries and want to eliminate JIT compilation overhead and compiler requirements. The package is permissively licensed and has no known vulnerabilities. However, maintenance is aging (last release 214 days ago), so verify compatibility with your specific torch and library versions before relying on it in production. If you don't use DLPack or have no performance concerns around initialization, it offers no benefit."},"id":"torch-c-dlpack-ext","links":{"html":"https://skillfed.io/packages/torch-c-dlpack-ext","md":"https://skillfed.io/packages/torch-c-dlpack-ext.md","pypi":"https://pypi.org/project/torch-c-dlpack-ext/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-12","license_spdx":null,"license_treatment":"permissive","name":"torch-c-dlpack-ext","python_support":"supports_current","summary":"torch c dlpack ext"},"popularity":{"monthly_downloads":4777053,"position":2233,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.1.5"}