Py之fvcorefvcore库的简介、安装、使用方法之详细攻略

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Py之fvcore:fvcore库的简介、安装、使用方法之详细攻略

目录

fvcore库的简介

fvcore库的安装

fvcore库的使用方法

1、基础用法

fvcore库的简介

fvcore是一个轻量级的核心库,它提供了在各种计算机视觉框架(如Detectron2)中共享的最常见和最基本的功能。这个库基于Python 3.6+和PyTorch。这个库中的所有组件都经过了类型注释、测试和基准测试。Facebook 的人工智能实验室即FAIR的计算机视觉组负责维护这个库。

github地址:https://github.com/facebookresearch/fvcore

fvcore库的安装

pip install -U 'git+https://github.com/facebookresearch/fvcore'

fvcore库的使用方法

1、基础用法

"""Configs."""

from fvcore.common.config import CfgNode

# -----------------------------------------------------------------------------

# Config definition

# -----------------------------------------------------------------------------

_C = CfgNode()

# ---------------------------------------------------------------------------- #

# Batch norm options

# ---------------------------------------------------------------------------- #

_C.BN = CfgNode()

# BN epsilon.

Py之fvcore:fvcore库的简介、安装、使用方法之详细攻略

_C.BN.EPSILON = 1e-5

# BN momentum.

_C.BN.MOMENTUM = 0.1

# Precise BN stats.

_C.BN.USE_PRECISE_STATS = False

# Number of samples use to compute precise bn.

_C.BN.NUM_BATCHES_PRECISE = 200

# Weight decay value that applies on BN.

_C.BN.WEIGHT_DECAY = 0.0

# ---------------------------------------------------------------------------- #

# Training options.

# ---------------------------------------------------------------------------- #

_C.TRAIN = CfgNode()

# If True Train the model, else skip training.

_C.TRAIN.ENABLE = True

# Dataset.

_C.TRAIN.DATASET = "kinetics"

# Total mini-batch size.

_C.TRAIN.BATCH_SIZE = 64

# Evaluate model on test data every eval period epochs.

_C.TRAIN.EVAL_PERIOD = 1

# Save model checkpoint every checkpoint period epochs.

_C.TRAIN.CHECKPOINT_PERIOD = 1

# Resume training from the latest checkpoint in the output directory.

_C.TRAIN.AUTO_RESUME = True

# Path to the checkpoint to load the initial weight.

_C.TRAIN.CHECKPOINT_FILE_PATH = ""

# Checkpoint types include `caffe2` or `pytorch`.

_C.TRAIN.CHECKPOINT_TYPE = "pytorch"

# If True, perform inflation when loading checkpoint.

_C.TRAIN.CHECKPOINT_INFLATE = False

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