Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

rnnsynth stalls out #5

Open
aferriss opened this issue Nov 18, 2015 · 11 comments
Open

rnnsynth stalls out #5

aferriss opened this issue Nov 18, 2015 · 11 comments

Comments

@aferriss
Copy link

when I run rnnsynth I get this output that looks like it's loading all the weights from my model, but then it starts to load sequences and just hangs. I looked into activity monitor and rnnsynth drops down to 0% cpu. Here's my output:

$ rnnsynth trained/synth1d2015.11.16-22.46.13.644782.best_loss.save 
task = prediction

network:
task = prediction
11VerticalNet
------------------------------
5 layers:
10InputLayer "input" 1D (+) size 3
(R) 11Lstm1dLayerI4TanhS0_8LogisticE "hidden_0_0" 1D (+) inputSize 1600 outputSize 400 source "input" 1200 peeps
(R) 11Lstm1dLayerI4TanhS0_8LogisticE "hidden_1_0" 1D (+) inputSize 1600 outputSize 400 source "hidden_0_0" 1200 peeps
(R) 11Lstm1dLayerI4TanhS0_8LogisticE "hidden_2_0" 1D (+) inputSize 1600 outputSize 400 source "hidden_1_0" 1200 peeps
20MixtureSamplingLayer "output" 1D (+) size 121 source "hidden_2_0"
------------------------------
20 connections:
"bias_to_output" (121 wts)
"hidden_2_0_to_output" (48400 wts)
"hidden_0_0_to_output" (48400 wts)
"hidden_1_0_to_output" (48400 wts)
"bias_to_charwindow_0" (30 wts)
"hidden_0_0_to_charwindow_0" (12000 wts)
"bias_to_hidden_0_0" (1600 wts)
"hidden_0_0_to_hidden_0_0_delay_-1" (640000 wts)
"input_to_hidden_0_0" (4800 wts)
"charwindow_0_to_hidden_0_0_delay_-1" (92800 wts)
"bias_to_hidden_1_0" (1600 wts)
"hidden_1_0_to_hidden_1_0_delay_-1" (640000 wts)
"hidden_0_0_to_hidden_1_0" (640000 wts)
"input_to_hidden_1_0" (4800 wts)
"charwindow_0_to_hidden_1_0" (92800 wts)
"bias_to_hidden_2_0" (1600 wts)
"hidden_2_0_to_hidden_2_0_delay_-1" (640000 wts)
"hidden_1_0_to_hidden_2_0" (640000 wts)
"input_to_hidden_2_0" (4800 wts)
"charwindow_0_to_hidden_2_0" (92800 wts)
------------------------------
bidirectional = false
symmetry = false
3658551 weights

setting random seed to 4203834845

loading dynamic data from trained/synth1d2015.11.16-22.46.13.644782.best_loss.save
loading trainer.epoch
loading trainer.mdlPriorMean
loading trainer.mdlPriorVariance
loading weightContainer.bias_to_charwindow_0__mdl_devs
loading weightContainer.bias_to_charwindow_0__mdl_weight_costs
loading weightContainer.bias_to_charwindow_0_mdl_dev_optimiser_deltas
loading weightContainer.bias_to_charwindow_0_mdl_dev_optimiser_g
loading weightContainer.bias_to_charwindow_0_mdl_dev_optimiser_n
loading weightContainer.bias_to_charwindow_0_weight_optimiser_deltas
loading weightContainer.bias_to_charwindow_0_weight_optimiser_g
loading weightContainer.bias_to_charwindow_0_weight_optimiser_n
loading weightContainer.bias_to_charwindow_0_weights
loading weightContainer.bias_to_hidden_0_0__mdl_devs
loading weightContainer.bias_to_hidden_0_0__mdl_weight_costs
loading weightContainer.bias_to_hidden_0_0_mdl_dev_optimiser_deltas
loading weightContainer.bias_to_hidden_0_0_mdl_dev_optimiser_g
loading weightContainer.bias_to_hidden_0_0_mdl_dev_optimiser_n
loading weightContainer.bias_to_hidden_0_0_weight_optimiser_deltas
loading weightContainer.bias_to_hidden_0_0_weight_optimiser_g
loading weightContainer.bias_to_hidden_0_0_weight_optimiser_n
loading weightContainer.bias_to_hidden_0_0_weights
loading weightContainer.bias_to_hidden_1_0__mdl_devs
loading weightContainer.bias_to_hidden_1_0__mdl_weight_costs
loading weightContainer.bias_to_hidden_1_0_mdl_dev_optimiser_deltas
loading weightContainer.bias_to_hidden_1_0_mdl_dev_optimiser_g
loading weightContainer.bias_to_hidden_1_0_mdl_dev_optimiser_n
loading weightContainer.bias_to_hidden_1_0_weight_optimiser_deltas
loading weightContainer.bias_to_hidden_1_0_weight_optimiser_g
loading weightContainer.bias_to_hidden_1_0_weight_optimiser_n
loading weightContainer.bias_to_hidden_1_0_weights
loading weightContainer.bias_to_hidden_2_0__mdl_devs
loading weightContainer.bias_to_hidden_2_0__mdl_weight_costs
loading weightContainer.bias_to_hidden_2_0_mdl_dev_optimiser_deltas
loading weightContainer.bias_to_hidden_2_0_mdl_dev_optimiser_g
loading weightContainer.bias_to_hidden_2_0_mdl_dev_optimiser_n
loading weightContainer.bias_to_hidden_2_0_weight_optimiser_deltas
loading weightContainer.bias_to_hidden_2_0_weight_optimiser_g
loading weightContainer.bias_to_hidden_2_0_weight_optimiser_n
loading weightContainer.bias_to_hidden_2_0_weights
loading weightContainer.bias_to_output__mdl_devs
loading weightContainer.bias_to_output__mdl_weight_costs
loading weightContainer.bias_to_output_mdl_dev_optimiser_deltas
loading weightContainer.bias_to_output_mdl_dev_optimiser_g
loading weightContainer.bias_to_output_mdl_dev_optimiser_n
loading weightContainer.bias_to_output_weight_optimiser_deltas
loading weightContainer.bias_to_output_weight_optimiser_g
loading weightContainer.bias_to_output_weight_optimiser_n
loading weightContainer.bias_to_output_weights
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1__mdl_devs
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1__mdl_weight_costs
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_g
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_n
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_weight_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_weight_optimiser_g
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_weight_optimiser_n
loading weightContainer.charwindow_0_to_hidden_0_0_delay_-1_weights
loading weightContainer.charwindow_0_to_hidden_1_0__mdl_devs
loading weightContainer.charwindow_0_to_hidden_1_0__mdl_weight_costs
loading weightContainer.charwindow_0_to_hidden_1_0_mdl_dev_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_1_0_mdl_dev_optimiser_g
loading weightContainer.charwindow_0_to_hidden_1_0_mdl_dev_optimiser_n
loading weightContainer.charwindow_0_to_hidden_1_0_weight_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_1_0_weight_optimiser_g
loading weightContainer.charwindow_0_to_hidden_1_0_weight_optimiser_n
loading weightContainer.charwindow_0_to_hidden_1_0_weights
loading weightContainer.charwindow_0_to_hidden_2_0__mdl_devs
loading weightContainer.charwindow_0_to_hidden_2_0__mdl_weight_costs
loading weightContainer.charwindow_0_to_hidden_2_0_mdl_dev_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_2_0_mdl_dev_optimiser_g
loading weightContainer.charwindow_0_to_hidden_2_0_mdl_dev_optimiser_n
loading weightContainer.charwindow_0_to_hidden_2_0_weight_optimiser_deltas
loading weightContainer.charwindow_0_to_hidden_2_0_weight_optimiser_g
loading weightContainer.charwindow_0_to_hidden_2_0_weight_optimiser_n
loading weightContainer.charwindow_0_to_hidden_2_0_weights
loading weightContainer.hidden_0_0_peepholes__mdl_devs
loading weightContainer.hidden_0_0_peepholes__mdl_weight_costs
loading weightContainer.hidden_0_0_peepholes_mdl_dev_optimiser_deltas
loading weightContainer.hidden_0_0_peepholes_mdl_dev_optimiser_g
loading weightContainer.hidden_0_0_peepholes_mdl_dev_optimiser_n
loading weightContainer.hidden_0_0_peepholes_weight_optimiser_deltas
loading weightContainer.hidden_0_0_peepholes_weight_optimiser_g
loading weightContainer.hidden_0_0_peepholes_weight_optimiser_n
loading weightContainer.hidden_0_0_peepholes_weights
loading weightContainer.hidden_0_0_to_charwindow_0__mdl_devs
loading weightContainer.hidden_0_0_to_charwindow_0__mdl_weight_costs
loading weightContainer.hidden_0_0_to_charwindow_0_mdl_dev_optimiser_deltas
loading weightContainer.hidden_0_0_to_charwindow_0_mdl_dev_optimiser_g
loading weightContainer.hidden_0_0_to_charwindow_0_mdl_dev_optimiser_n
loading weightContainer.hidden_0_0_to_charwindow_0_weight_optimiser_deltas
loading weightContainer.hidden_0_0_to_charwindow_0_weight_optimiser_g
loading weightContainer.hidden_0_0_to_charwindow_0_weight_optimiser_n
loading weightContainer.hidden_0_0_to_charwindow_0_weights
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1__mdl_devs
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1__mdl_weight_costs
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_deltas
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_g
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_mdl_dev_optimiser_n
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_weight_optimiser_deltas
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_weight_optimiser_g
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_weight_optimiser_n
loading weightContainer.hidden_0_0_to_hidden_0_0_delay_-1_weights
loading weightContainer.hidden_0_0_to_hidden_1_0__mdl_devs
loading weightContainer.hidden_0_0_to_hidden_1_0__mdl_weight_costs
loading weightContainer.hidden_0_0_to_hidden_1_0_mdl_dev_optimiser_deltas
loading weightContainer.hidden_0_0_to_hidden_1_0_mdl_dev_optimiser_g
loading weightContainer.hidden_0_0_to_hidden_1_0_mdl_dev_optimiser_n
loading weightContainer.hidden_0_0_to_hidden_1_0_weight_optimiser_deltas
loading weightContainer.hidden_0_0_to_hidden_1_0_weight_optimiser_g
loading weightContainer.hidden_0_0_to_hidden_1_0_weight_optimiser_n
loading weightContainer.hidden_0_0_to_hidden_1_0_weights
loading weightContainer.hidden_0_0_to_output__mdl_devs
loading weightContainer.hidden_0_0_to_output__mdl_weight_costs
loading weightContainer.hidden_0_0_to_output_mdl_dev_optimiser_deltas
loading weightContainer.hidden_0_0_to_output_mdl_dev_optimiser_g
loading weightContainer.hidden_0_0_to_output_mdl_dev_optimiser_n
loading weightContainer.hidden_0_0_to_output_weight_optimiser_deltas
loading weightContainer.hidden_0_0_to_output_weight_optimiser_g
loading weightContainer.hidden_0_0_to_output_weight_optimiser_n
loading weightContainer.hidden_0_0_to_output_weights
loading weightContainer.hidden_1_0_peepholes__mdl_devs
loading weightContainer.hidden_1_0_peepholes__mdl_weight_costs
loading weightContainer.hidden_1_0_peepholes_mdl_dev_optimiser_deltas
loading weightContainer.hidden_1_0_peepholes_mdl_dev_optimiser_g
loading weightContainer.hidden_1_0_peepholes_mdl_dev_optimiser_n
loading weightContainer.hidden_1_0_peepholes_weight_optimiser_deltas
loading weightContainer.hidden_1_0_peepholes_weight_optimiser_g
loading weightContainer.hidden_1_0_peepholes_weight_optimiser_n
loading weightContainer.hidden_1_0_peepholes_weights
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1__mdl_devs
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1__mdl_weight_costs
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_mdl_dev_optimiser_deltas
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_mdl_dev_optimiser_g
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_mdl_dev_optimiser_n
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_weight_optimiser_deltas
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_weight_optimiser_g
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_weight_optimiser_n
loading weightContainer.hidden_1_0_to_hidden_1_0_delay_-1_weights
loading weightContainer.hidden_1_0_to_hidden_2_0__mdl_devs
loading weightContainer.hidden_1_0_to_hidden_2_0__mdl_weight_costs
loading weightContainer.hidden_1_0_to_hidden_2_0_mdl_dev_optimiser_deltas
loading weightContainer.hidden_1_0_to_hidden_2_0_mdl_dev_optimiser_g
loading weightContainer.hidden_1_0_to_hidden_2_0_mdl_dev_optimiser_n
loading weightContainer.hidden_1_0_to_hidden_2_0_weight_optimiser_deltas
loading weightContainer.hidden_1_0_to_hidden_2_0_weight_optimiser_g
loading weightContainer.hidden_1_0_to_hidden_2_0_weight_optimiser_n
loading weightContainer.hidden_1_0_to_hidden_2_0_weights
loading weightContainer.hidden_1_0_to_output__mdl_devs
loading weightContainer.hidden_1_0_to_output__mdl_weight_costs
loading weightContainer.hidden_1_0_to_output_mdl_dev_optimiser_deltas
loading weightContainer.hidden_1_0_to_output_mdl_dev_optimiser_g
loading weightContainer.hidden_1_0_to_output_mdl_dev_optimiser_n
loading weightContainer.hidden_1_0_to_output_weight_optimiser_deltas
loading weightContainer.hidden_1_0_to_output_weight_optimiser_g
loading weightContainer.hidden_1_0_to_output_weight_optimiser_n
loading weightContainer.hidden_1_0_to_output_weights
loading weightContainer.hidden_2_0_peepholes__mdl_devs
loading weightContainer.hidden_2_0_peepholes__mdl_weight_costs
loading weightContainer.hidden_2_0_peepholes_mdl_dev_optimiser_deltas
loading weightContainer.hidden_2_0_peepholes_mdl_dev_optimiser_g
loading weightContainer.hidden_2_0_peepholes_mdl_dev_optimiser_n
loading weightContainer.hidden_2_0_peepholes_weight_optimiser_deltas
loading weightContainer.hidden_2_0_peepholes_weight_optimiser_g
loading weightContainer.hidden_2_0_peepholes_weight_optimiser_n
loading weightContainer.hidden_2_0_peepholes_weights
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1__mdl_devs
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1__mdl_weight_costs
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_mdl_dev_optimiser_deltas
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_mdl_dev_optimiser_g
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_mdl_dev_optimiser_n
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_weight_optimiser_deltas
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_weight_optimiser_g
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_weight_optimiser_n
loading weightContainer.hidden_2_0_to_hidden_2_0_delay_-1_weights
loading weightContainer.hidden_2_0_to_output__mdl_devs
loading weightContainer.hidden_2_0_to_output__mdl_weight_costs
loading weightContainer.hidden_2_0_to_output_mdl_dev_optimiser_deltas
loading weightContainer.hidden_2_0_to_output_mdl_dev_optimiser_g
loading weightContainer.hidden_2_0_to_output_mdl_dev_optimiser_n
loading weightContainer.hidden_2_0_to_output_weight_optimiser_deltas
loading weightContainer.hidden_2_0_to_output_weight_optimiser_g
loading weightContainer.hidden_2_0_to_output_weight_optimiser_n
loading weightContainer.hidden_2_0_to_output_weights
loading weightContainer.input_to_hidden_0_0__mdl_devs
loading weightContainer.input_to_hidden_0_0__mdl_weight_costs
loading weightContainer.input_to_hidden_0_0_mdl_dev_optimiser_deltas
loading weightContainer.input_to_hidden_0_0_mdl_dev_optimiser_g
loading weightContainer.input_to_hidden_0_0_mdl_dev_optimiser_n
loading weightContainer.input_to_hidden_0_0_weight_optimiser_deltas
loading weightContainer.input_to_hidden_0_0_weight_optimiser_g
loading weightContainer.input_to_hidden_0_0_weight_optimiser_n
loading weightContainer.input_to_hidden_0_0_weights
loading weightContainer.input_to_hidden_1_0__mdl_devs
loading weightContainer.input_to_hidden_1_0__mdl_weight_costs
loading weightContainer.input_to_hidden_1_0_mdl_dev_optimiser_deltas
loading weightContainer.input_to_hidden_1_0_mdl_dev_optimiser_g
loading weightContainer.input_to_hidden_1_0_mdl_dev_optimiser_n
loading weightContainer.input_to_hidden_1_0_weight_optimiser_deltas
loading weightContainer.input_to_hidden_1_0_weight_optimiser_g
loading weightContainer.input_to_hidden_1_0_weight_optimiser_n
loading weightContainer.input_to_hidden_1_0_weights
loading weightContainer.input_to_hidden_2_0__mdl_devs
loading weightContainer.input_to_hidden_2_0__mdl_weight_costs
loading weightContainer.input_to_hidden_2_0_mdl_dev_optimiser_deltas
loading weightContainer.input_to_hidden_2_0_mdl_dev_optimiser_g
loading weightContainer.input_to_hidden_2_0_mdl_dev_optimiser_n
loading weightContainer.input_to_hidden_2_0_weight_optimiser_deltas
loading weightContainer.input_to_hidden_2_0_weight_optimiser_g
loading weightContainer.input_to_hidden_2_0_weight_optimiser_n
loading weightContainer.input_to_hidden_2_0_weights
epoch = 3

loading sequences from 0 to 10748

It never moves past this point. I didn't let my networks train until 20 epochs, but would that make a difference here? Does rnnsynth need any additional input parameters? I did notice this line during the CMAKE build process but assumed it was fine with the library that it found

NO MKL Libs using: /Users/aferriss/Desktop/rnnlib/install/lib/libopenblas.a
@szcom
Copy link
Owner

szcom commented Nov 29, 2015

Do you have verbose output turned on either in .save file verbose=true or in command line --verbose=true?

@aferriss
Copy link
Author

@szcom Hmm, I just checked and looks like verbose is set to false. Would setting verbose to true hang things up? I'm starting to think there is nothing in the sequences that it's trying to load, so it gets there and looks for things but never finds any and just sits waiting...

I'm guessing this fails somewhere in the load_sequences function in the NetcdfDataset.hpp between line 338 and 341 because I'm never seeing any console output after

COUT << "loading sequences from " << first << " to " << last << endl;

@szcom
Copy link
Owner

szcom commented Nov 30, 2015

@aferriss i was suggesting to use verbose=true to see if there is anything else being printed out or it is the end of it. You can play with --dataFraction=.001 to skip loading all of the dataset

is it possible to attach gdb and see the stack trace? may be some clues there

@aferriss
Copy link
Author

aferriss commented Dec 1, 2015

@szcom Ah well I feel a little foolish now. I didn't realize I had to pass the test string in via stdin when running rnnsynth. Still not working properly though. If I do --sentence="some sentence" it just hangs like before. But If I do

rnnsynth my.bestModel.save <<< "some test text"

It loads my model and seems to start working but then...

loading sequences from 0 to 10748
sentence:just a little test here
generating samples from network
Sample -0.196839 -0.00302385 0
Sample 0.499858 -0.0109408 0
Sample -0.664826 0.507392 1
Sample -1.04247 -1.17686 0
Sample -0.295973 0.233749 0
Sample -0.660129 0.402054 0
Sample -0.634767 0.42037 0
Sample -0.531624 0.180569 0
Sample -0.0125981 0.317507 0
Sample -0.092688 0.379909 0
Sample 0.0470404 0.27367 1
Sample -0.0672439 -0.0672392 0
Sample -0.0748704 -0.344124 0
End of sentence

ERRROR: add --sentence=<what>

saving to aborted.save

And then it quits.

I'm not that familiar with gdb, but I'll give that a try to see if it sheds light on anything. Would it be like:

gdb rnnsynth
(gdb) run myModel.save

ctrl-c at the hang and then

(gdb) backtrace

edit: I just did what I wrote down about for gdb and it spat this out for me

loading sequences from 0 to 10748
sentence:test words
generating samples from network
Sample -0.196839 -0.00302385 0
Sample 0.769625 0.744073 0
Sample 0.0677519 1.19304 0
Sample 1.10804 -0.485457 0
Sample 0.827261 -0.492805 0
Sample -0.237702 -0.0489046 0
End of sentence

ERRROR: add --sentence=<what>

saving to aborted.save
^C[New Thread 0x1713 of process 17556]
[New Thread 0x1803 of process 17556]
[New Thread 0x1903 of process 17556]

Program received signal SIGINT, Interrupt.
0x00007fff97c8597a in ?? () from /usr/lib/system/libsystem_kernel.dylib
(gdb) backtrace
#0  0x00007fff97c8597a in ?? () from /usr/lib/system/libsystem_kernel.dylib
#1  0x00007fff95de69ed in _swrite () from /usr/lib/system/libsystem_c.dylib
#2  0x00007fff95de1db0 in __sfvwrite () from /usr/lib/system/libsystem_c.dylib
#3  0x00007fff95de20ab in fwrite () from /usr/lib/system/libsystem_c.dylib
#4  0x0000000100012758 in std::__1::basic_filebuf<char, std::__1::char_traits<char> >::overflow(int) ()
#5  0x00007fff8eca291d in std::__1::basic_streambuf<char, std::__1::char_traits<char> >::xsputn(char const*, long) ()
   from /usr/lib/libc++.1.dylib
#6  0x00007fff8ecc2db1 in std::__1::ostreambuf_iterator<char, std::__1::char_traits<char> > std::__1::__pad_and_output<char, std::__1::char_traits<char> >(std::__1::ostreambuf_iterator<char, std::__1::char_traits<char> >, char const*, char const*, char const*, std::__1::ios_base&, char) () from /usr/lib/libc++.1.dylib
#7  0x00007fff8ecc34d0 in std::__1::num_put<char, std::__1::ostreambuf_iterator<char, std::__1::char_traits<char> > >::do_put(std::__1::ostreambuf_iterator<char, std::__1::char_traits<char> >, std::__1::ios_base&, char, double) const ()
   from /usr/lib/libc++.1.dylib
#8  0x00007fff8eca910a in std::__1::basic_ostream<char, std::__1::char_traits<char> >::operator<<(float) ()
   from /usr/lib/libc++.1.dylib
#9  0x000000010003e13a in RangeVal<std::__1::pair<std::__1::__wrap_iter<float*>, std::__1::__wrap_iter<float*> > >::print(std::__1::basic_ostream<char, std::__1::char_traits<char> >&) const ()
#10 0x0000000100013af5 in DataExporter::save(std::__1::basic_ostream<char, std::__1::char_traits<char> >&) const ()
#11 0x00000001000102ac in dumpState() ()
#12 0x000000010001c08b in main ()

@szcom
Copy link
Owner

szcom commented Dec 4, 2015

under gdb it dies if you stop on a breakpoint and try to continue...

@melserafy
Copy link

what you need is to write your sentence on the screen after line
loading sequences from 0 to 10748
such as " hi mohamed"
then press enter

@aferriss
Copy link
Author

@melserafy ah that was it, I feel silly now. Didn't realize it was waiting for input. Thanks!

@melserafy
Copy link

@aferriss did the rnnsynth give the right sentence output
because the number of points is always equal the number of character and the show_pen never draw the handwritten sentence

@aferriss
Copy link
Author

@melserafy I'm not entirely sure because I didn't train the network for the full amount of epochs so I just get some weird jibberish. It didn't seem like it was giving the right amount of samples however. For instance:

sentence:test
generating samples from network
Sample -0.196839 -0.00302385 0
Sample -0.27598 0.627462 0
Sample -0.47703 0.985082 0
Sample -0.347154 1.17401 0
Sample -0.285182 1.00471 0
Sample -0.174918 0.647909 0
Sample -0.138178 0.518378 0
Sample -0.16205 0.212179 0
Sample -0.157472 -0.0650334 0
Sample -0.118352 0.0956962 0
Sample -0.0355938 -0.0749825 0
Sample 0.000652945 -0.157771 0
Sample 0.125519 -0.471247 0
Sample 0.175422 -0.579012 0
Sample 0.234026 -0.555993 0
End of sentence
test test
sentence:test test
generating samples from network
Sample -0.196839 -0.00302385 0
Sample -0.287154 0.335853 0
Sample -0.211068 0.733722 0
Sample -0.235874 0.917814 0
Sample -0.292066 0.937081 0
Sample -0.373799 0.920008 1
Sample -1.07679 -0.183297 1
Sample -0.341941 0.492819 0
Sample -0.244001 -0.0357202 0
End of sentence

Why would "test test" generate fewer samples than just "test"?

If I run "test test" again I get a longer one, but it seems to alternate between shorter and longer sample outputs.

test test
sentence:test test
generating samples from network
Sample -0.196839 -0.00302385 0
Sample -0.0838182 0.204657 0
Sample -0.227178 0.0771148 0
Sample -0.14238 0.675532 0
Sample -0.303252 1.03711 0
Sample -0.282828 1.25808 0
Sample -0.207127 1.13021 0
Sample -0.190784 0.785013 0
Sample -0.0776912 0.708522 1
Sample -0.623038 -1.45835 1
Sample 0.207126 0.160342 0
Sample 0.314539 -0.0371642 0
Sample 0.206288 -0.114421 0
Sample 0.213798 -0.168228 1
Sample 1.16016 -1.73765 1
Sample -0.0967172 -0.467515 0
Sample 0.0533866 -0.450783 0
Sample 0.171299 -0.714265 0
Sample 0.267934 -0.92481 0
Sample 0.133314 -1.09226 0
Sample -0.0575374 -1.0629 0
Sample -0.345903 -0.763908 0
Sample -0.985898 -0.507829 0
Sample -0.469195 0.0819529 0
Sample -0.437748 0.0287031 0
Sample -0.230258 0.46517 0
Sample -0.30988 1.10226 0
Sample -0.414899 1.73108 0
Sample -0.502445 2.1108 0
End of sentence

@ghost
Copy link

ghost commented Apr 20, 2016

when running rnnsynth how do you save the output?

@aferriss
Copy link
Author

aferriss commented Apr 21, 2016

@andkylrob you can just send it to a text file. rnnsynth is just printing to stdout anyway. so:

rnnsynth myModel > output.txt

should work, but keep in mind you won't see any output on the terminal since it's being sent to a file. You could see both by piping to tee I think

rnnsynth mymodel | tee output.txt

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants