    NET-SPEC:  Create a new network, or display specifications for existing net.

    Net-spec creates a log file containing records describing the network
    architecture and the associated priors.  When invoked with just a log
    file as argument, it displays the specifications of the network stored
    in that log file.

    Usage:

        net-spec log-file N-inputs { N-hidden { flag } } N-outputs { flag }
                 / ti [ ih bh th { hh ih bh th } ] { ho } io bo  [ / { ah } ao ]
    or:

        net-spec log-file

    N-inputs and N-outputs are the numbers of units in the input and
    output layers.  The sizes of zero or more hidden layers are specified
    between these.  Flags pertaining to a layer may be specified after the
    argument giving the size of the layer.

    The following flag is supported for hidden layers and the output
    layer:

        omit:[-]<input>{,<input>}

    This specifies that connections from certain inputs are to be omitted
    from those feeding into this layer (assuming that any inputs at all
    are looked at, as specifed by later arguments).  If the "-" is placed
    before the list of inputs, the list gives the inputs that are NOT
    omitted.  Inputs are numbered starting with 1.

    For hidden layers, the activation function to use may be specified
    using one of the following flags:

        tanh identity sin

    The default is tanh, the hyperbolic tangent function.  The identity
    flag causes the output of a hidden unit in the layer to be identical
    its summed input.  The sin flag specifies that the activation function
    to be h(u) = sqrt(2)*sin(sqrt(2)*u).  The multiplications by sqrt(2)
    in this activation function make a network with one hidden layer of
    this type correspond in the limit of many hidden units to a Gaussian
    process model with covariance function given by exp(-distance^2).

    Following a "/", the priors for groups of weights, biases, and offsets
    are specified.  "ti" is the prior for the offsets of input units, "hh"
    the prior for hidden-hidden weights, "ih" the prior for input-hidden
    weights, "bh" the prior for hidden biases, "th" the prior for hidden
    unit offsets, "ho" the prior for weights from a hidden layer to the
    outputs, "io" the prior for input-output weights, and "bo" the prior
    for output biases.  The order of priors relating to hidden layers is
    from the first layer to the last (the last being the one closest to
    the output layer).  All the priors relating to a network with the
    given number of hidden layers must be present, except that some or all
    of the hidden-output priors may be omitted.  The order of "ho" priors
    is last to first; if not all are present, it is the priors for
    connections from the earlier layers that are absent.

    For the syntax of a prior specification, see prior.doc.  If "-" is
    given instead of a prior specification (or, for "ho" priors, if they
    are omitted entirely), the parameters in question do not exist at all,
    which is equivalent to their being zero.

    The alpha values that specify the prior for the "adjustments" to the
    distributions of weights and biases going into a given unit are
    specified following these priors.  A value of "-" corresponds to
    infinity (effectively eliminating the adjustment).  The entire set of
    adjustments may be omitted, eliminating them all.

    Note that a data model will also have to be specified (with model-spec)
    if any learning is to be done.

    Two records are written to the newly created log file - one with type
    'A' with a net_arch structure as data, and one with type 'P' with a
    net_priors structure as data.  A record of type 'F' will be written as
    well if any flags were specified.  These records have an index of -1.
    When the second form of the command is used (with just the log file as
    argument), these records are read and the information they contain is
    displayed on standard output.

                Copyright (c) 1995-2003 by Radford M. Neal