diff --git a/aimodel/slurm-TEST-deeplabv3p-rainfall.job b/aimodel/slurm-TEST-deeplabv3p-rainfall.job
index 51298ea..f794e60 100755
--- a/aimodel/slurm-TEST-deeplabv3p-rainfall.job
+++ b/aimodel/slurm-TEST-deeplabv3p-rainfall.job
@@ -1,7 +1,7 @@
 #!/usr/bin/env bash
 #SBATCH -J DeepRain
 #SBATCH -N 1
-#SBATCH -n 14
+#SBATCH -n 9
 #SBATCH --gres=gpu:1
 #SBATCH -o %j.%N.%a.deeplab-rainfall.out.log
 #SBATCH -e %j.%N.%a.deeplab-rainfall.err.log
@@ -21,7 +21,21 @@ command_exists() {
 
 #######################################################
 
-if command_exists module; then
+if [[ "${SLURM_CLUSTER_NAME}" == "cs-cluster" ]]; then
+	echo "[slurm_runner] csgpu cluster detected, applying CUDA workarounds" >&2;
+	# Fix "Could not load library libcublasLt.so.12. Error: libcublasLt.so.12: cannot open shared object file: No such file or directory" error
+	if [[ -d "${HOME}/cuda" ]]; then
+		echo "[slurm_runner] sourcing extra CUDA setup script" >&2;
+		#shellcheck source=/dev/null
+		source "${HOME}/cuda/activate.sh";
+	fi
+	
+	export XLA_FLAGS="--xla_gpu_cuda_data_dir=/usr/lib/cuda"; # weird... this wasn't needed before? Fixes 
+	echo "[slurm_runner] set XLA_FLAGS=\"${XLA_FLAGS}\"" >&2;
+fi
+
+# No modules on the CS cluster
+if command_exists module && [[ "${SLURM_CLUSTER_NAME}" != "cs-cluster" ]]; then
 	module load utilities/multi
 	module load readline/7.0
 	module load gcc/10.2.0
@@ -30,7 +44,7 @@ if command_exists module; then
 	
 	module load python/anaconda/4.6/miniconda/3.7
 else
-	echo "[slurm_runner]: module command not present, not loading modules" >&2;
+	echo "[slurm_runner]: module command not present or csgpu cluster detected, not loading modules" >&2;
 fi
 
 
@@ -74,7 +88,7 @@ show_help() {
 	exit;
 }
 
-DIR_RAINFALLWATER="${DIR_RAINFALLWATER:-$HOME/rainfallwater_records_tfrecord}";
+DIR_RAINFALLWATER="${DIR_RAINFALLWATER:-$HOME/data/rainfallwater_records_tfrecord}";
 PATH_HEIGHTMAP="${PATH_HEIGHTMAP:-$HOME/data/terrain50-nimrodsized.json.gz}";
 PATH_COLOURMAP="${PATH_COLOURMAP:-$HOME/data/instance-level-human-parsing/instance-level_human_parsing/human_colormap.mat}";
 
@@ -92,6 +106,9 @@ mkdir -p "${DIR_OUTPUT}";
 echo -e ">>> NOW: $(date)";
 echo -e ">>> DIR_OUTPUT: ${DIR_OUTPUT}";
 echo -e ">>> Additional args: ${ARGS}";
+echo -e ">>> GIT COMMIT: $(git rev-parse HEAD)";
+
+{ echo "*****"; git rev-parse HEAD; git status; git log -1 | cat; } >>"${DIR_OUTPUT}/commit.txt";
 
 export PATH=$HOME/software/bin:$PATH;
 export IMAGE_SIZE BATCH_SIZE DIR_RAINFALLWATER PATH_HEIGHTMAP PATH_COLOURMAP STEPS_PER_EPOCH DIR_OUTPUT PATH_CHECKPOINT EPOCHS PREDICT_COUNT NO_REMOVE_ISOLATED_PIXELS LOSS LEARNING_RATE DICE_LOG_COSH WATER_THRESHOLD UPSAMPLE STEPS_PER_EXECUTION JIT_COMPILE RANDSEED PREDICT_AS_ONE SPLIT_VALIDATE SPLIT_TEST;
diff --git a/aimodel/src/deeplabv3_plus_test_rainfall.py b/aimodel/src/deeplabv3_plus_test_rainfall.py
index 8e0f3cb..5ba6640 100755
--- a/aimodel/src/deeplabv3_plus_test_rainfall.py
+++ b/aimodel/src/deeplabv3_plus_test_rainfall.py
@@ -20,7 +20,7 @@ import matplotlib.pyplot as plt
 
 import tensorflow as tf
 
-import lib.primitives.env
+import lib.primitives.env as env
 from lib.dataset.dataset_mono import dataset_mono, dataset_mono_predict
 from lib.ai.components.LossCrossEntropyDice import LossCrossEntropyDice
 from lib.ai.components.MetricDice import metric_dice_coefficient as dice_coefficient
@@ -40,7 +40,7 @@ logger.info(f"Starting at {str(datetime.now().isoformat())}")
 # ███████ ██   ████   ████   ██ ██   ██  ██████  ██   ████ ██      ██ ███████ ██   ████    ██
 
 IMAGE_SIZE = env.read("IMAGE_SIZE", int, 128)  # was 512; 128 is the highest power of 2 that fits the data
-BATCH_SIZE = env.read("BATCH_SIZE", int, 64)
+BATCH_SIZE = env.read("BATCH_SIZE", int, 32)
 NUM_CLASSES = 2
 DIR_RAINFALLWATER = env.read("DIR_RAINFALLWATER", str)
 PATH_HEIGHTMAP = env.read("PATH_HEIGHTMAP", str)
@@ -48,10 +48,10 @@ PATH_COLOURMAP = env.read("PATH_COLOURMAP", str)
 PARALLEL_READS = env.read("PARALLEL_READS", float, 1.5)
 STEPS_PER_EPOCH = env.read("STEPS_PER_EPOCH", int, None)
 REMOVE_ISOLATED_PIXELS = env.read("NO_REMOVE_ISOLATED_PIXELS", bool, True)
-EPOCHS = env.read("EPOCHS", int, 50)
+EPOCHS = env.read("EPOCHS", int, 25)
 LOSS = env.read("LOSS", str, "cross-entropy-dice")  # other possible values: cross-entropy
 DICE_LOG_COSH = env.read("DICE_LOG_COSH", bool, False)
-LEARNING_RATE = env.read("LEARNING_RATE", float, 0.001)
+LEARNING_RATE = env.read("LEARNING_RATE", float, 0.00001)
 WATER_THRESHOLD = env.read("WATER_THRESHOLD", float, 0.1)
 UPSAMPLE = env.read("UPSAMPLE", int, 2)
 SPLIT_VALIDATE = env.read("SPLIT_VALIDATE", float, 0.2)
@@ -59,7 +59,7 @@ SPLIT_TEST = env.read("SPLIT_TEST", float, 0)
 # NOTE: RANDSEED is declared and handled in src/lib/dataset/primitives/shuffle.py
 
 STEPS_PER_EXECUTION = env.read("STEPS_PER_EXECUTION", int, 1)
-JIT_COMPILE = env.read("JIT_COMPILE", bool, False)
+JIT_COMPILE = env.read("JIT_COMPILE", bool, True)
 DIR_OUTPUT = env.read("DIR_OUTPUT", str, f"output/{datetime.utcnow().date().isoformat()}_deeplabv3plus_rainfall_TEST")
 PATH_CHECKPOINT = env.read("PATH_CHECKPOINT", str, None)
 PREDICT_COUNT = env.read("PREDICT_COUNT", int, 25)
@@ -95,7 +95,7 @@ if not PREDICT_AS_ONE:
 		do_remove_isolated_pixels=REMOVE_ISOLATED_PIXELS,
 		parallel_reads_multiplier=PARALLEL_READS,
 		percentage_validate=SPLIT_VALIDATE,
-		percentage_test=SPLIT_TESTs
+		percentage_test=SPLIT_TEST
 	)
 
 	logger.info("Train Dataset:", dataset_train)
diff --git a/aimodel/src/lib/dataset/dataset_mono.py b/aimodel/src/lib/dataset/dataset_mono.py
index 7e5e8b3..1a428be 100644
--- a/aimodel/src/lib/dataset/dataset_mono.py
+++ b/aimodel/src/lib/dataset/dataset_mono.py
@@ -165,7 +165,7 @@ def dataset_mono(dirpath_input, percentage_validate=0.2, percentage_test=0, **kw
 	filepaths_count = len(filepaths)
 	
 	split_trainvalidate=math.floor(filepaths_count * (1-(percentage_validate+percentage_test)))
-	split_validatetest=math.floor(filepaths * (1 - percentage_test))
+	split_validatetest=math.floor(filepaths_count * (1 - percentage_test))
 	
 	
 	filepaths_train = filepaths[:split_trainvalidate]
diff --git a/aimodel/src/lib/primitives/env.py b/aimodel/src/lib/primitives/env.py
index 7ab0c3a..c90928e 100644
--- a/aimodel/src/lib/primitives/env.py
+++ b/aimodel/src/lib/primitives/env.py
@@ -8,6 +8,7 @@ import os
 ###
 
 ## Changelog:
+# 2024-11-14: Fix crash on line #107 unterminated string literal
 # 2024-09-29: Create this changelog, prepare for reuse
 
 ##############################################################################
@@ -104,8 +105,7 @@ def print_all(table=True):
 	
 	
 	# Create the table format string
-	format_string = f"| {{:<{width_name}}} | {{:<{
-		width_type}}} | {{:<{width_value}}} | {{:<{width_flags}}} |"
+	format_string = f"| {{:<{width_name}}} | {{:<{width_type}}} | {{:<{width_value}}} | {{:<{width_flags}}} |"
 
 	# Calculate total width
 	total_width = width_name + width_type + width_value + \