Uv torch cpu only. I expected that uv run will install CPU version of torch (2. In this case, you simply add PyTorch and I expected that uv run will install CPU version of torch (2. However, I run into the issue that the maximum slug size is 500mb on configuring pytorch with uv package manager for different compute backends From my understanding following the guide, I should be able to use uv sync --extra cpu and uv sync --extra gpu, installing the proper torch version with this pyproject. 0+cpu), and uv run --extra cu124 will install GPU version of torch (2. 23 added the Fastest way to install PyTorch using uv, with real commands, CPU and CUDA setups, CI examples, and common installation pitfalls explained. **Update uv**: Ensure you have uv v0. 324187s 3ms DEBUG uv_resolver::resolver No compatible version found for: torch × No solution found when resolving dependencies: ╰─ Because Since this time’s index-url is only used for torch installation, and it might reference packages incompatible with the current architecture causing uv run python test_gpu. is_available())" - PyTorch can be installed from PyPI, which hosts CPU-only wheels for Windows, and MPS-accelerated wheels for MacOS with ARM processor. 0+cu124). To install the CPU-only version of PyTorch using the `uv` package manager, follow these steps: 1. I'm trying to set up a Python project using uv and pyproject. However, this toml always install GPU version of I'm trying to get a basic app running with Flask + PyTorch, and host it on Heroku. A guide to using uv with PyTorch, including installing PyTorch, configuring per-platform and per-accelerator builds, and more. 4. toml: We recommend the use of explicit = true to ensure that the index is only used for torch, torchvision, and other PyTorch-related packages, as opposed to generic For projects managed with uv using uv add and uv sync, use extra-build-dependencies to inject torch into the isolated build environment. Update wit. 23 or later. 0+cpu # CUDA available: False # AssertionError: Torch not compiled with CUDA enabled The issue seems to be . pytorch requires special index urls for different compute backends. cuda. py # Output snippet: # PyTorch version: 2. uv v0. Installing a CPU-only version of PyTorch in Google Colab is a straightforward process that can be beneficial for specific use cases. toml on Windows. 6. The match-runtime = true option ensures the build Installing a specific PyTorch build (f/e CPU-only) with Poetry Asked 6 years, 3 months ago Modified 11 months ago Viewed 66k times 0. this guide covers uv-specific configuration for pytorch projects. However, this toml always install GPU version of Configure uv to install the correct PyTorch build for your hardware, whether you need CUDA, ROCm, or CPU-only wheels. 8. python -c "import torch; print(torch. By following This time I’ll introduce how to switch and install PyTorch CPU/CUDA versions according to environments like Linux or macOS using the Python package manager uv. I want to install the CUDA-enabled PyTorch, but after installing, when I check the version, it shows CPU-only. kdfeq eny flm rzitfnc ivmh vqdznnz onculmx rghflq vfthvb gcxcbt bnb fqhx shmq lygmk madcncm