GMTKDMLPTRAIN(1)

NAME
gmtkDMLPtrain - a Graphical Models Toolkit (GMTK) 1.4.4 program

SYNOPSIS
gmtkDMLPtrain [[[-flag] [option]] ...]

DESCRIPTION
This program trains deep neural networks for use with DeepVECPTs.

OPTIONS
Required: <>; Optional: []; Flagless arguments must be in order.

Observation input file handling:

<-ofX str>
    Observation File. Replace X with the file number {null}

[-nfX unsigned]
    Number of floats in observation file X {0}

[-niX unsigned]
    Number of ints in observation file X {0}

[-fmtX str]
    Format (htk,binary,ascii,flatascii,hdf5,pfile) for observation file X {pfile}

[-fileBufferSize unsigned]
    Size in MB of the file observation frame buffer {16}

[-constantSpace bool]
    Use only fileBufferSize memory to hold the observation data {F}

[-fileWindowSize unsigned]
    Size in MB to load at once if constantSpace is active {4}

[-fileWindowDelta unsigned]
    How close (in frames) from the edge of the current window triggers loading more frames {100}

[-iswpX bool]
    Endian swap condition for observation file X {T}

[-prefrX str]
    Float range for observation file X (before transforms) {all}

[-preirX str]
    Int range for observation file X {all}

[-frX str]
    Float range for observation file X (after transforms) {all}

[-irX str]
    Int range for observation file X {all}

[-srX str]
    Segment range for observation file X {all}

[-leftPadX unsigned]
    Prepend padding frames to file X {0}

[-rightPadX unsigned]
    Append padding frames to file X {0}

[-preprX str]
    Pre Per-segment frame Range for obs file X before any transforms are applied {null}

[-postprX str]
    Post Per-segment frame Range for obs file X after per-stream transforms are applied {null}

[-gpr str]
    Global Per-segment final frame Range {null}

[-justification str]
    Justification of usable frames (left, center, right) {left}

[-obsNAN bool]
    True if observation files allow FP NAN values {F}

File range options:

[-trrng str]
    Range to train over segment file {all}

[-startSkip integer]
    Frames to skip at beginning (i.e., first frame is buff[startSkip]) {0}

[-endSkip integer]
    Frames to skip at end (i.e., last frame is buff[len-1-endSkip]) {0}

Help options:

[-help [unsigned]]
    Print this message. Add an argument from 1 to 5 for increasing help info. {1}

[-version bool]
    Print GMTK version number and exit. {F}

Observation matrix transformation options:

[-fdiffactX str]
    Action if different number of frames in streams: error (er), repeat last frame (rl), first frame (rf), segmentally expand (se), truncate from start (ts), truncate from end (te) {er}

[-sdiffactX str]
    Action if different number of segments in streams: error (er), truncate from end (te), repeat last sent (rl), and wrap around (wa). {te}

[-cppifascii bool]
    Pre-process ASCII files using CPP {F}

[-transX str]
    per stream transformations string {null}

[-posttrans str]
    Final global transformations string {null}

[-comb str]
    Combine float features (none: no combination, add, sub, mul,div {none}

[-cppCommandOptions str]
    Command line options to give to 'cpp' {null}

Input trainable parameter file handling:

[-inputMasterFile str]
    Input file of multi-level master CPP processed GM input parameters {null}

[-outputMasterFile str]
    Output file to place master CPP processed GM output parameters {null}

[-inputTrainableParameters str]
    File of only and all trainable parameters {null}

[-binInputTrainableParameters bool]
    Binary condition of trainable parameters file {F}

[-outputTrainableParameters str]
    File to place only and all trainable output parametes {null}

[-binOutputTrainableParameters bool]
    Binary condition of output trainable parameters? {F}

[-allocateDenseCpts integer]
    Automatically allocate undefined CPTs. (-1) = don't read params, (0) = don't allocate, (1) = use random initial CPT values, (2) = use uniform values {0}

[-cptNormThreshold double]
    Read error if |Sum-1.0|/card > norm_threshold {1.000000e-02}

Continuous random variable options:

[-varFloor double]
    Variance Floor (variances can't fall below this value) {1.000000e-10}

[-floorVarOnRead bool]
    Floor the variances to varFloor when they are read in {F}

General options:

[-seed bool]
    Seed the random number generator {F}

[-verbosity str]
    Verbosity - coma separated list of m=v, where m is all, default, inference, inference-memory, training, triangulation, boundary, unrolling, printing, modelinfo, obsfile, obsstream; 0 <= v <= 100 {null}

[-printIntValues bool]
    Always print rv values as integer rather than symbols {F}

DMLP training options:

[-nnChunkSize unsigned]
    Size in MB to use for incremental DeepNN matrix operations {4}

[-batchQueueSize unsigned]
    Size (in training instances) of the asynchronous batch queue {1000}

<-deepMLPName str>
    Name of deep NN to train {null}

[-featureOffset unsigned]
    Offset in observation file where input features start {0}

<-numFeatures unsigned>
    Number of input features (per frame) {0}

[-radius unsigned]
    Number of frames comprising one input instance = 2r+1 {0}

<-labelOffset unsigned>
    Offset in observation file where output labels start {0}

[-oneHot bool]
    If true, labelOffset is the single discrete correct parent value, else the parent distribution starts ate labelOffset {T}

[-randomInitLayer bool]
    Initialize weights randomly (according to sparse or dense strategy specified by -sparseInitLayer) {T}

[-sparseInitLayer bool]
    Use sparse or dense initilization strategy (dense is better for rectified linear) {F}

[-trainingSchedule str]
    Order to process training data (linear, random, permute, shuffle) {linear}

[-pretrainType str]
    Pretraining type (none, AE, CD) {CD}

[-pretrainActFunc str]
    Pretraining input activation function (sig, tanh, cubic, linear, rect) {linear}

[-saveTrainingFile str]
    Filename to save training state for resuming training later {null}

[-loadTrainingFile str]
    Filename to load training state from to resume training {null}

[-tempDir str]
    Directory to store temp files if $GMTKTMPDIR environment variable is not set {null}

DMLP pretraining hyperparameters:

[-ptInitStepSize double]
    Pretrain: Initial step size hyperparameter {1.000000e-02}

[-ptMinMomentum double]
    Pretrain: Minimum momentum hyperparameter {5.000000e-01}

[-ptMaxMomentum double]
    Pretrain: Maximum momentum hyperparameter {9.900000e-01}

[-ptMaxUpdate double]
    Pretrain: Maximum update hyperparameter {1.000000e-01}

[-ptL2 double]
    Pretrain: l2 hyperparameter {0.000000e+00}

[-ptNumEpochs float]
    Pretrain: Number of epochs hyperparameter {1.000000e+00}

[-ptNumAnnealEpochs float]
    Pretrain: Number of anneal epochs hyperparameter {1.000000e+00}

[-ptMiniBatchSize unsigned]
    Pretrain: Mini-batch size hyperparameter {10}

[-ptCheckInterval unsigned]
    Pretrain: Check interval hyperparameter {2000}

DMLP backprob hyperparameters:

[-bpInitStepSize double]
    Backprop: Initial step size hyperparameter {1.000000e-02}

[-bpMinMomentum double]
    Backprop: Minimum momentum hyperparameter {5.000000e-01}

[-bpMaxMomentum double]
    Backprop: Maximum momentum hyperparameter {9.900000e-01}

[-bpMaxUpdate double]
    Backprop: Maximum update hyperparameter {1.000000e-01}

[-bpL2 double]
    Backprop: l2 hyperparameter {0.000000e+00}

[-bpNumEpochs float]
    Backprop: Total epochs of training hyperparameter {1.000000e+00}

[-bpEpochFraction float]
    Backprop: [0,1] fraction of -bpNumEpochs to do in this invocation {1.000000e+00}

[-bpNumAnnealEpochs float]
    Backprop: Total epochs of anneal training hyperparameter {1.000000e+00}

[-bpAnnealEpochFraction float]
    Backprop: [0,1] fraction of -bpNumAnnealEpochs to do in this invocation {1.000000e+00}

[-bpMiniBatchSize unsigned]
    Backprop: Mini-batch size hyperparameter {10}

[-bpCheckInterval unsigned]
    Backprop: Check interval hyperparameter {2000}

[-bpIdropP double]
    Backprop: dropout probability for input layer {0.000000e+00}

[-bpHdropP double]
    Backprop: dropout probability for hidden layers {0.000000e+00}

Additional arguments:

[-argsFile <str>]
    File to obtain additional arguments from {}

Mercurial id: 2e685b02ff37 checkin date: Fri Dec 04 02:13:34 2015 -0800

ENVIRONMENT

GMTKTMPDIR
    Temporary directory gmtkDMLPtrain uses to store neural network parameters

GMTK_CPP_CMD
    Command GMTK programs use to preprocess ASCII input files

GMTK_GZIP_CMD
    Command GMTK programs use to uncompress ASCII input files with ".gz" extensions

GMTK_BZIP2_CMD
    Command GMTK programs ue to uncompress ASCII input files with ".bz2" extensions

REPORTING BUGS
Report bugs to http://j.ee.washington.edu/trac/gmtk

COPYRIGHT
Copyright © 2001-2015 Jeff Bilmes

Licensed under the Open Software License version 3.0
See COPYING or http://opensource.org/licenses/OSL-3.0

SEE ALSO
The GMTK source code and full documentation is available at
http://melodi.ee.washington.edu/gmtk

Support is availabe via the GMTK Users' mailing list
gmtk-users@u.washington.edu

Subscribe at
http://mailman.u.washington.edu/mailman/listinfo/gmtk-users