diff --git a/aimodel/src/subcommands/pretrain_predict.py b/aimodel/src/subcommands/pretrain_predict.py
index 9577aa3..2a3694f 100644
--- a/aimodel/src/subcommands/pretrain_predict.py
+++ b/aimodel/src/subcommands/pretrain_predict.py
@@ -8,8 +8,8 @@ import re
 from loguru import logger
 import tensorflow as tf
 import numpy as np
-from lib.io.writefile import writefile
 
+from lib.io.writefile import writefile
 from lib.io.handle_open import handle_open
 from lib.ai.RainfallWaterContraster import RainfallWaterContraster
 from lib.dataset.dataset import dataset_predict
@@ -76,11 +76,14 @@ def run(args):
 		write_mode = "wb"
 	
 	handle = sys.stdout
+	filepath_params = None
 	if filepath_output != "-":
 		handle = handle_open(
 			filepath_output if args.records_per_file <= 0 else filepath_output.replace("$d", 0),
 			write_mode
 		)
+		filepath_params = os.path.join(os.path.dirname(filepath_output), "/params.json")
+	
 	
 	i = 0
 	i_file = i
@@ -96,8 +99,11 @@ def run(args):
 		if output_mode == MODE_JSONL:
 			handle.write(json.dumps(step_rainfall.numpy().tolist(), separators=(',', ':'))+"\n") # Ref https://stackoverflow.com/a/64710892/1460422
 		elif output_mode == MODE_TFRECORD:
-			if i == 0:
-				writefile(json.dumps({ }))
+			if i == 0 and filepath_params is not None:
+				writefile(filepath_params, json.dumps({
+					"rainfallradar": step_rainfall.shape.as_list(),
+					"waterdepth": step_water.shape.as_list()
+				}))
 			step_rainfall = tf.train.BytesList(value=[tf.io.serialize_tensor(step_rainfall, name="rainfall").numpy()])
 			step_water = tf.train.BytesList(value=[tf.io.serialize_tensor(step_water, name="water").numpy()])