NAME

       caffe - command line brew for Caffe

SYNOPSIS

        caffe <COMMAND> <FLAGS>

DESCRIPTION

       Caffe  is  a deep learning framework made with expression, speed, and modularity in mind. It is developed
       by the Berkeley Vision and Learning Center (BVLC) and community contributors.

COMMANDS

       train  train or finetune a model

       test   score a model

       device_query
              show GPU diagnostic information

       time   benchmark model execution time

FREQUENTLY USED FLAGS

       -gpu   (Optional; run in GPU mode on given device IDs separated by ','.  Use '-gpu all'  to  run  on  all
              available  GPUs. The effective training batch size is multiplied by the number of devices.)  type:
              string default: ""

       -iterations
              (The number of iterations to run.) type: int32 default: 50

       -level (Optional; network level.) type: int32 default: 0

       -model (The model definition protocol buffer text file..) type: string default: ""

       -phase (Optional; network phase (TRAIN or TEST). Only used for 'time'.)  type: string default: ""

       -sighup_effect
              (Optional; action to take when a SIGHUP signal is received: snapshot, stop or none.) type:  string
              default: "snapshot"

       -sigint_effect
              (Optional;  action to take when a SIGINT signal is received: snapshot, stop or none.) type: string
              default: "stop"

       -snapshot
              (Optional; the snapshot solver state to resume training.)  type: string default: ""

       -solver
              (The solver definition protocol buffer text file.) type: string default: ""

       -stage (Optional; network stages (not to be  confused  with  phase),  separated  by  ','.)  type:  string
              default: ""

       -weights
              (Optional;  the  pretrained  weights  to  initialize  finetuning,  separated by ','. Cannot be set
              simultaneously with snapshot.)  type: string default: ""

       -help  Show complete help messages.

OTHER CAFFE UTILITIES

       Apart from the "caffe" command line utility, there are also some utilities available, run them with  "-h"
       or "--help" argument to see corresponding help.

       •  convert_imageset

       •  convert_cifar_data

       •  compute_image_mean

       •  convert_mnist_siamese_data

       •  upgrade_net_proto_binary

       •  extract_features

       •  upgrade_solver_proto_text

       •  classification

       •  upgrade_net_proto_text

       •  convert_mnist_data

EXAMPLES

       Train a new Network

           $ caffe train -solver solver.prototxt

       Resume training a network from a snapshot

           $ caffe train -solver solver.prototxt -snapshot bvlc_alexnet.solverstate

       Fine-tune a network

           $ caffe train -solver solver.prototxt -weights pre_trained.caffemodel

       Test (evaluate) a trained model for 100 iterations, on GPU 0

           $ caffe test -model train_val.prototxt -weights bvlc_alexnet.caffemodel -gpu 0 -iterations 100

       Run a benchmark against AlexNet on GPU 0

           $ caffe time -model deploy.prototxt -gpu 0

       Check CUDA device availability of GPU 0

           $ caffe device_query -gpu 0

HOMEPAGE

       http://caffe.berkeleyvision.org

BUGS

       https://github.com/BVLC/caffe/issues

AUTHOR

       This  manpage  is written by Zhou Mo <cdluminate@gmail.com> with the help of txt2man for Debian according
       to program's help message.

                                                 10 August 2016                                         CAFFE(1)