Add registry saving

ml_model.py

@@ -6,6 +6,8 @@ import os.path
 import mlflow
 import sys
 
+from mlflow.tracking import MlflowClient
+
 from tensorflow import keras
 from tensorflow.keras import layers
 from tensorflow.keras.layers.experimental import preprocessing
@@ -48,7 +50,12 @@ model.fit(train_X, train_Y, verbose=verbose, epochs=epochs)
 signature = mlflow.models.signature.infer_signature(train_X.numpy(), model.predict(train_X.numpy()))
 input_data = test_X
 
+
+# Dane do rejestracji modelu w MlFlow
+mlflow.set_tracking_uri("http://172.17.0.1:5000")
+client = MlflowClient()
+model_name = "s434704"
+
 with mlflow.start_run():
+    mlflow.keras.log_model(model, "movies_on_streaming_platforms_model", registered_model_name="s434704", input_example=input_data.numpy(), signature=signature)
     mlflow.keras.save_model(model, "movies_on_streaming_platforms_model", input_example=input_data.numpy(), signature=signature)
-
-