train diary with cross feature

src/train_diary.py

@@ -62,8 +62,7 @@ def main():
     estimator_config = tf.estimator.RunConfig(session_config=session_config)
 
     model = tf.estimator.Estimator(model_fn=esmm_model_fn, params=params, model_dir=model_path, config=estimator_config)
-    # TODO 50000
-    train_spec = tf.estimator.TrainSpec(input_fn=lambda: esmm_input_fn(train_df, shuffle=True), max_steps=15000)
+    train_spec = tf.estimator.TrainSpec(input_fn=lambda: esmm_input_fn(train_df, shuffle=True), max_steps=50000)
     eval_spec = tf.estimator.EvalSpec(input_fn=lambda: esmm_input_fn(val_df, shuffle=False))
     res = tf.estimator.train_and_evaluate(model, train_spec, eval_spec)
     print("@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@")
@@ -75,12 +74,11 @@ def main():
     model_export_path = str(Path("/data/files/models/diary").expanduser())
     save_path = model_export(model, all_features, model_export_path)
     print("save to: " + save_path)
-    # TODO save model
-    # set_essm_model_save_path("diary", save_path)
+    set_essm_model_save_path("diary", save_path)
     print("============================================================")
 
     # save_path = str(Path("~/Desktop/models/1596012827").expanduser())  # local
-    # save_path = "/data/files/models/diary/1598948682"  # server
+    # save_path = "/data/files/models/diary/1598952349"  # server
 
     # tf.saved_model.load