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Updated README.md
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README.md

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@@ -43,26 +43,36 @@ If you have <i>several datafiles</i> then you can do something like:
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# bash example of how to use the -r flag
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# see std_conf.h on how to change the default
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# behaviour before building the program.
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#
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# In this example, the source code
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# of the project will be given as
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# training data for the LSTM network.
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folder="THE FOLDER WITH THE FILES"
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first=1
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for file in $(ls -p $folder | grep -v /); do
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if [ $first -eq 1 ]; then
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# Train the net using new weights
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# a file with the name lstm_net.net
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# will appear, see std_conf.h
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# Store every 500 iterations,
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# train for 10000 iterations.
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./net $folder/$file -st 500 -it 10000
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first=0
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else
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# Train the net using previously trained weights
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# Store every 500 iterations,
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# train for 10000 iterations.
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./net $folder/$file -r lstm_net.net -st 500 -it 10000
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fi
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# Build
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make
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# How many cycles all source files are to be trained on
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CYCLES=10
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cycle=0
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# list source files
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files=$(ls *.h *.c)
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while [ $cycle -lt $CYCLES ]; do
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echo "$(date) Starting cycle $((cycle+1))"
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first=1
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for file in $files; do
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echo "$(date) starting to train on file: $file"
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if [ $first -eq 1 ]; then
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./net $file -vr 0 -it 10000 -st 5000 -N 64 -L 3
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first=0
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else
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./net $file -vr 0 -r lstm_net.net -it 10000 -st 5000
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fi
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done
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cycle=$((cycle+1))
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done
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echo "Finished!"
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</pre>
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## Windows
@@ -106,10 +116,12 @@ The following flags are available:
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-out: number of characters to output directly, note: a network and a datafile must be provided.
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-L : Number of layers, may not exceed 10
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-N : Number of neurons in every layer
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-vr : Verbosity level. Set to zero and only the loss function after and not during training will be printed.
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-c : Don't train, only generate output. Seed given by the value. If -r is used, datafile is not considered.
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Check std_conf.h to see what default values are used, these are set during compilation.
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./net compiled Dec 21 2019 15:55:28
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./net compiled Dec 23 2019 17:13:42
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</pre>
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