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.
