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authorInigoGutierrez <inigogf.95@gmail.com>2022-11-01 18:06:40 +0100
committerInigoGutierrez <inigogf.95@gmail.com>2022-11-01 18:06:40 +0100
commite8b9bf589e698b51e55ae59693b5bb0293f86a26 (patch)
tree0500d1af9972aa89067b6a08179cb973102b854b /doc/tex/results.tex
parent3b78e9f3751dfc7c77a7d137d0dbab04afcb23f5 (diff)
downloadimago-e8b9bf589e698b51e55ae59693b5bb0293f86a26.tar.gz
imago-e8b9bf589e698b51e55ae59693b5bb0293f86a26.zip
Added SGF and GTP instances as acronyms.
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1 files changed, 2 insertions, 2 deletions
diff --git a/doc/tex/results.tex b/doc/tex/results.tex
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@@ -102,14 +102,14 @@ so no more are shown here.
\subsection{Neural Network Training}
-Each network has been training by receiving batches of SGF files which are first
+Each network has been training by receiving batches of \acrshort{sgf} files which are first
converted to lists of moves by the Training System and then provided to the
train function of the networks. This has been executed with the following
command:
\inputminted[fontsize=\small]{bash}{listings/trainCommand.sh}
-Which lists the contents of a folder containing multiple SGF files, shuffles the
+Which lists the contents of a folder containing multiple \acrshort{sgf} files, shuffles the
list, takes some of them and passes them to train.py as arguments. The combined
list of game positions and moves made from them in all the games selected make
up the sample of the training. The number of files selected can of course be