Package dimer :: Package nnet :: Module monitor :: Class LearnMonitor

Class LearnMonitor

       object --+    
                |    
          Monitor --+
                    |
   object --+       |
            |       |
        tuple --+   |
                |   |
??.learnmonitor-1 --+
                    |
                   LearnMonitor

learning stats

Instance Methods

[hide private]

Inherited from unreachable.learnmonitor: __getnewargs__, __repr__

Inherited from unreachable.learnmonitor (private): _asdict, _replace

Inherited from tuple: __add__, __contains__, __eq__, __ge__, __getattribute__, __getitem__, __getslice__, __gt__, __hash__, __iter__, __le__, __len__, __lt__, __mul__, __ne__, __rmul__, __sizeof__, count, index

Inherited from object: __delattr__, __format__, __init__, __reduce__, __reduce_ex__, __setattr__, __str__, __subclasshook__

Class Methods

[hide private]

_from_fs(cls, ds, mtr, epoch, cost_f, ce_f, mcl_f)

source code

Inherited from Monitor: is_max_down, is_max_still, is_max_up, is_min_down, is_min_still, is_min_up, rel_diff

Inherited from Monitor (private): _archive_dump, _dump, _empty, _has_changed

Inherited from unreachable.learnmonitor (private): _make

Static Methods

[hide private]

Inherited from unreachable.learnmonitor: __new__

Class Variables

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_ftypes = (<type 'int'>, <type 'float'>, <type 'float'>, <type...

_report_frm = 'Epoch {epoch} / lrate: {lrate:.6f}\n\tCost: {tr...

Inherited from Monitor: ftype_frm, fzero

Inherited from unreachable.learnmonitor (private): _fields

Properties

[hide private]

Inherited from Monitor: csv, report

Inherited from unreachable.learnmonitor: epoch, lrate, trainCE, trainMC, traincost, validCE, validMC, validcost

Inherited from object: __class__

Class Variable Details

[hide private]

_ftypes

Value:

(<type 'int'>,
 <type 'float'>,
 <type 'float'>,
 <type 'float'>,
 <type 'float'>,
 <type 'float'>,
 <type 'float'>,
 <type 'float'>)

_report_frm

Value:

'''Epoch {epoch} / lrate: {lrate:.6f}
\tCost: {traincost:.6f} / {validcost:.6f} 
\tCross entropy: {trainCE:.6f} / {validCE:.6f} 
\tMissclass.: {trainMC:.2%} / {validMC:.2%}'''