{"library":"fvcore","type":"library","category":null,"description":"fvcore is a lightweight core library that provides common and essential functionalities shared across various computer vision frameworks developed by FAIR (Facebook AI Research), such as Detectron2, PySlowFast, and ClassyVision. It includes features like PyTorch layers, hierarchical flop/parameter counting tools, checkpointing utilities, configuration management, and hyperparameter schedulers. The library is actively maintained by the FAIR computer vision team and features type-annotated, tested, and benchmarked components.","language":"python","status":"active","version":"0.1.5.post20221221","tags":["computer vision","pytorch","utilities","facebook research","FAIR","model analysis","flops"],"last_verified":"Fri May 22","install":[{"cmd":"pip install -U fvcore","imports":["from fvcore.nn import FlopCountAnalysis","from fvcore.nn import ActivationCountAnalysis","from fvcore.common.config import CfgNode","from fvcore.common.registry import Registry","from fvcore.common.checkpoint import Checkpointer"]}],"homepage":null,"github":"https://github.com/facebookresearch/fvcore","docs":null,"changelog":null,"pypi":"https://pypi.org/project/fvcore/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":6.3,"avg_import_s":null,"wheel_type":"sdist"},"url":"https://checklist.day/v1/registry/fvcore/compatibility"}}