Provided by: caffe-tools-cpu_1.0.0-6_amd64 bug


       caffe - command line brew for Caffe


        caffe <COMMAND> <FLAGS>


       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.


       train  train or finetune a model

       test   score a model

              show GPU diagnostic information

       time   benchmark model execution time


       -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: ""

              (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: ""

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

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

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

              (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: ""

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

       -help  Show complete help messages.


       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


       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




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

                                          10 August 2016                                 CAFFE(1)