Including a script for preparing the pre-trained models.

Author: pengyunie

pretrain.sh

@@ -0,0 +1,77 @@
+#!/bin/bash
+
+_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
+
+
+# This script is for pre-training the models
+
+
+function process_data() {
+        local ds=$1; shift
+
+        ( cd $_DIR/python/
+          rm -rf $_DIR/output/$ds/data
+          python -m roosterize.main extract_data_from_corpus\
+                 --corpus=$_DIR/../math-comp-corpus\
+                 --output=$_DIR/output/$ds/data\
+                 --groups=$ds
+        )
+}
+
+function train_model() {
+        local ds=$1; shift
+        
+        ( cd $_DIR/python/
+          rm -rf $_DIR/output/$ds/model
+          python -m roosterize.main train_model\
+                 --train=$_DIR/output/$ds/data/$ds-train\
+                 --val=$_DIR/output/$ds/data/$ds-val\
+                 --model-dir=$_DIR/output/$ds/model\
+                 --output=$_DIR/output/$ds/data\
+                 --config-file=$_DIR/configs/Stmt+ChopKnlTree+attn+copy.json
+        )
+}
+
+function package_model() {
+        local ds=$1; shift
+        
+        ( cd $_DIR/output/$ds/
+          tar czf roosterize-model-$ds.tgz model/
+        )
+}
+
+function eval_model() {
+        local ds=$1; shift
+        
+        ( cd $_DIR/python/
+          rm -rf $_DIR/output/$ds/results
+          python -m roosterize.main eval_model\
+                 --data=$_DIR/output/$ds/data/$ds-test\
+                 --model-dir=$_DIR/output/$ds/model\
+                 --output=$_DIR/output/$ds/results
+        )
+}
+
+function retrain_all_models() {
+        for ds in t1 ta; do
+                process_data $ds
+                train_model $ds
+                package_model $ds
+        done
+}
+
+
+# ==========
+# Main function -- program entry point
+# This script can be executed as ./run.sh the_function_to_run
+
+function main() {
+        local action=${1:?Need Argument}; shift
+
+        ( cd ${_DIR}
+          $action "$@"
+        )
+}
+
+main "$@"
+