Search Results for "path-setting"

...Allow you to override the Go version with an environment variable. Search commands from multiple versions of Go at a time. At a high level, goenv intercepts Go commands using shim executables injected into your PATH, determines which Go version has been specified by your application, and passes your commands along to the correct Go installation. When you run all the variety of Go commands using go, your operating system searches through a list of directories to find an executable file with that name. This list of directories lives in an environment variable called PATH, with each directory in the list separated by a colon.

update-golang is a script to easily fetch and install new Golang releases with minimum system intrusion. The script uses local system OS and ARCH to download the correct binary release. It is not harmful to run the script multiple times. Downloaded releases are kept as cache under '/usr/local'. You can erase them manually. By default, the script only detects actual releases (not beta releases, not release candidates). However one can force any specific non-final release. The default behavior...

...It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration on Mac directly through Metal. The README and releases emphasized this was a macOS-optimized distribution, not an upstream fork of TensorFlow, and it cataloged common installation notes and issues encountered by early Apple Silicon users. In practice, the repo served as a bridge during the transition to native Mac acceleration, making modern TensorFlow viable on Apple hardware while upstream support matured.

RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. ...