{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/17"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/10"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/8"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/21"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"Enables PyTorch to use DirectML for GPU acceleration on DirectX 12-compatible hardware from AMD, Intel, NVIDIA, and Qualcomm.","skillfed_tags":["gpu-acceleration","directml","pytorch-backend"],"use_cases":["Train PyTorch models on Windows machines with AMD or Intel GPUs where CUDA is unavailable.","Run inference on DirectX 12-capable hardware without installing vendor-specific GPU drivers.","Prototype machine learning on consumer-grade GPUs (AMD, Intel, Qualcomm) before deploying to NVIDIA infrastructure.","Accelerate PyTorch workloads in Windows Subsystem for Linux environments with GPU support.","Evaluate multi-vendor GPU compatibility for a PyTorch application without rewriting code."],"what_it_does":"torch-directml is a PyTorch backend plugin that routes computation to DirectML, a hardware-accelerated DirectX 12 library maintained by Microsoft. It allows PyTorch models to train and run inference on a broad range of GPUs\u2014AMD, Intel, NVIDIA, and Qualcomm\u2014without requiring CUDA or vendor-specific drivers, making it particularly useful on Windows and Windows Subsystem for Linux systems where CUDA may not be available or practical.\n\nThe package is in active development (classified as Alpha) and depends on torch and torchvision. It provides pre-built wheels for Python 3.7 through 3.12 on both Windows and Linux, though operator coverage is still expanding. The project collects GPU device info and CPU fallback data to improve operator support, and it is maintained by Microsoft with an open issue tracker and active community feedback channels.","worth_installing":"Yes, if you are on Windows or WSL with a DirectX 12-capable GPU and need PyTorch acceleration without CUDA. The package is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and is backed by Microsoft. However, operator coverage is still developing\u2014verify that your specific PyTorch operations are supported via the operator roadmap before committing to production use."},"id":"torch-directml","links":{"html":"https://skillfed.io/packages/torch-directml","md":"https://skillfed.io/packages/torch-directml.md","pypi":"https://pypi.org/project/torch-directml/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-09-15","license_spdx":null,"license_treatment":"permissive","name":"torch-directml","python_support":"supports_current","summary":"A DirectML backend for hardware acceleration in PyTorch."},"popularity":{"monthly_downloads":88718,"position":13709,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.5.dev240914"}