Loaded file
./tess4training-save/tess4training-vedic/tessdata/best/Devanagari.lstm,
unpacking...

Warning: LSTMTrainer deserialized an LSTMRecognizer!

Code range changed from 217 to 157!!

Num (Extended) outputs,weights in Series:

1,48,0,1:1, 0

Num (Extended) outputs,weights in Series:

C3,3:9, 0

Ft16:16, 160

Total weights = 160

[C3,3Ft16]:16, 160

Mp3,3:16, 0

Lfys64:64, 20736

Lfx64:64, 33024

Lrx64:64, 33024

Lfx512:512, 1181696

Fc157:157, 80541

Total weights = 1349181

Previous null char=2 mapped to 2

Continuing from
./tess4training-save/tess4training-vedic/tessdata/best/Devanagari.lstm


​See the line:

​Code range changed from 217 to 157!!

That is the size of the unicharset. That is what is used in Fc.



ShreeDevi
____________________________________________________________
भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com

On Wed, Aug 23, 2017 at 2:48 PM, <[email protected]> wrote:

> Year, I have observed the builted network at beginning of the training
> step. Thanks for reply.
>
> The basetrain.log file shows that  Built network:[1,48,0,1 [C3,3 Ft16]
> Mp3,3 Lfys64 Lfx96 Lrx96 Lfx512 Fc209] from request [1,48,0,1 Ct3,3,16
> Mp3,3 Lfys64 Lfx96 Lrx96 Lfx512 O1c1]
>
> Some problms for understanding this builted network:
>
> 1. [C3,3 Ft16] layers in the network has been enclosed in brackets. But
> why it is enclosed in brackets? What does it stand for with the brackets?
> 2. Fc209 the last layer of this network is a Fully-connected layer.
> what's the meanings of the 'c' in this layer? I cannot find what 'Fc'
> represents in the VGSLSpecs tutorial.
>
> Thanks.
>
>
>
> 在 2017年8月23日星期三 UTC+8下午3:00:00,shree写道:
>>
>> I think that number is ignored and the actual number generated from
>> unichasrset is used.
>>
>> Usually there will be a message right at beginning of training showing
>> the number being used.
>>
>> On 23-Aug-2017 12:21 PM, <[email protected]> wrote:
>>
>>> Hello,
>>>
>>> I have pulled out the network of the chi_sim.traineddata with the
>>> command:  combine_tessdata -u ../../tessdata/chi_sim.traineddata
>>> ../../chi_sim_comp
>>>
>>> Then I observe the network which is shown in the chi_sim_comp file. The
>>> network is [1,48,0,1Ct3,3,16 Mp3,3 Lfys64 Lfx96 Lrx96 Lfx512 O1c1]
>>>
>>> By analyzing the VGSL Specs language, I can infer that the output layer
>>> of the network is O1c1, which means that Output layer produces 1-d
>>> (sequence) output, trained with CTC,*outputting 1 class*.
>>>
>>>
>>> Why does the output layer end up in one category? Whether the network
>>> structure recorded in the chi_sim.traineddata will be wrong?
>>>
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