309  pytorch(1) - Kailash Tool Reference

309.1 pytorch

pytorch - PyTorch — tensors and dynamic neural networks (CPU default; cuda variant via overlay).

Layer OPS
Category o-05-ai-engineering-sdks-dev-env
Safety class safe
Licence BSD-3-Clause
Upstream github.com/pytorch/pytorch

309.1.1 NAME

pytorch - PyTorch — tensors and dynamic neural networks (CPU default; cuda variant via overlay).

309.1.2 SYNOPSIS & usage

Derived from the upstream README at generation time; verify against --help where the tool is installed.

$ source <CONDA_INSTALL_DIR>/bin/activate
$ conda create -y -n <CONDA_NAME>
$ conda activate <CONDA_NAME>
$ source <CONDA_INSTALL_DIR>\Scripts\activate.bat
$ conda create -y -n <CONDA_NAME>
$ conda activate <CONDA_NAME>
$ call "C:\Program Files\Microsoft Visual Studio\<VERSION>\Community\VC\Auxiliary\Build\vcvarsall.bat" x64

309.1.3 DESCRIPTION (upstream)

PyTorch is a Python package that provides two high-level features: - Tensor computation (like NumPy) with strong GPU acceleration - Deep neural networks built on a tape-based autograd system You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed. Our trunk health (Continuous Integration signals) can be found at hud.pytorch.org. - More About PyTorch - A GPU-Ready Tensor Library - Dynamic Neural Networks: Tape-Based Autograd - Python First - [Imperative Experiences](#imperati

309.1.4 CONFIGURATION (detected)

Config-surface markers detected in the upstream README (15 matches, e.g. environment variable, environment variables). A full config reference page for this tool is queued under the config-page policy — this line is the detection record, not the page.

309.1.5 SEE ALSO

ref: pin - verified 2026-10-14