[DRAFT] Add model and experiment template 'click' options to dfp example pipelines, and make model names Databricks compatible.

examples/digital_fingerprinting/production/morpheus/dfp/utils/dfp_arg_parser.py

@@ -46,6 +46,8 @@ def __init__(self,
                  source: str,
                  tracking_uri: str,
                  silence_monitors: bool,
+                 mlflow_experiment_name_formatter: str,
+                 mlflow_model_name_formatter: str,
                  train_users: str = None):
 
         self._skip_users = list(skip_user)
@@ -65,8 +67,8 @@ def __init__(self,
         self._time_fields: TimeFields = None
         self._silence_monitors = silence_monitors
 
-        self._model_name_formatter = f"DFP-{source}-" + "{user_id}"
-        self._experiment_name_formatter = f"dfp/{source}/training/" + "{reg_model_name}"
+        self._model_name_formatter = mlflow_model_name_formatter
+        self._experiment_name_formatter = mlflow_experiment_name_formatter
 
     @staticmethod
     def verify_init(func):

examples/digital_fingerprinting/production/morpheus/dfp_azure_pipeline.py

@@ -140,6 +140,14 @@
               type=str,
               default="http://mlflow:5000",
               help=("The MLflow tracking URI to connect to the tracking backend."))
+@click.option('--mlflow_experiment_name_template',
+              type=str,
+              default="dfp/azure/training/{reg_model_name}",
+              help="The MLflow experiment name template to use when logging experiments. ")
+@click.option('--mlflow_model_name_template',
+              type=str,
+              default="DFP-azure-{user_id}",
+              help="The MLflow model name template to use when logging models. ")
 def run_pipeline(train_users,
                  skip_user: typing.Tuple[str],
                  only_user: typing.Tuple[str],
@@ -149,6 +157,8 @@ def run_pipeline(train_users,
                  log_level,
                  sample_rate_s,
                  filter_threshold,
+                 mlflow_experiment_name_template,
+                 mlflow_model_name_template,
                  **kwargs):
     """Runs the DFP pipeline."""
     # To include the generic, we must be training all or generic
@@ -311,8 +321,8 @@ def run_pipeline(train_users,
     # Output is UserMessageMeta -- Cached frame set
     pipeline.add_stage(DFPPreprocessingStage(config, input_schema=preprocess_schema))
 
-    model_name_formatter = "DFP-azure-{user_id}"
-    experiment_name_formatter = "dfp/azure/training/{reg_model_name}"
+    model_name_formatter = mlflow_model_name_template
+    experiment_name_formatter = mlflow_experiment_name_template
 
     if (is_training):
         # Finally, perform training which will output a model

examples/digital_fingerprinting/production/morpheus/dfp_duo_pipeline.py

@@ -141,6 +141,14 @@
               type=str,
               default="http://mlflow:5000",
               help=("The MLflow tracking URI to connect to the tracking backend."))
+@click.option('--mlflow_experiment_name_template',
+              type=str,
+              default="dfp/duo/training/{reg_model_name}",
+              help="The MLflow experiment name template to use when logging experiments. ")
+@click.option('--mlflow_model_name_template',
+              type=str,
+              default="DFP-duo-{user_id}",
+              help="The MLflow model name template to use when logging models. ")
 def run_pipeline(train_users,
                  skip_user: typing.Tuple[str],
                  only_user: typing.Tuple[str],
@@ -150,6 +158,8 @@ def run_pipeline(train_users,
                  log_level,
                  sample_rate_s,
                  filter_threshold,
+                 mlflow_experiment_name_template,
+                 mlflow_model_name_template,
                  **kwargs):
     """Runs the DFP pipeline."""
     # To include the generic, we must be training all or generic
@@ -306,8 +316,8 @@ def run_pipeline(train_users,
     # Output is UserMessageMeta -- Cached frame set
     pipeline.add_stage(DFPPreprocessingStage(config, input_schema=preprocess_schema))
 
-    model_name_formatter = "DFP-duo-{user_id}"
-    experiment_name_formatter = "dfp/duo/training/{reg_model_name}"
+    model_name_formatter = mlflow_model_name_template
+    experiment_name_formatter = mlflow_experiment_name_template
 
     if (is_training):
 

examples/digital_fingerprinting/production/morpheus/dfp_integrated_training_batch_pipeline.py

@@ -101,6 +101,14 @@
               type=str,
               default="http://mlflow:5000",
               help=("The MLflow tracking URI to connect to the tracking backend."))
+@click.option('--mlflow_experiment_name_template',
+              type=str,
+              default="dfp/{source}/training/{reg_model_name}",
+              help="The MLflow experiment name template to use when logging experiments. ")
+@click.option('--mlflow_model_name_template',
+              type=str,
+              default="DFP-{source}-{user_id}",
+              help="The MLflow model name template to use when logging models. ")
 @click.option("--disable_pre_filtering",
               is_flag=True,
               help=("Enabling this option will skip pre-filtering of json messages. "
@@ -126,6 +134,8 @@ def run_pipeline(source: str,
                  tracking_uri,
                  silence_monitors,
                  use_cpp,
+                 mlflow_experiment_name_template,
+                 mlflow_model_name_template,
                  **kwargs):
     if (skip_user and only_user):
         logging.error("Option --skip_user and --only_user are mutually exclusive. Exiting")
@@ -140,6 +150,8 @@ def run_pipeline(source: str,
                                   source,
                                   tracking_uri,
                                   silence_monitors,
+                                  mlflow_experiment_name_template,
+                                  mlflow_model_name_template,
                                   train_users)
 
     dfp_arg_parser.init()

examples/digital_fingerprinting/production/morpheus/dfp_integrated_training_streaming_pipeline.py

@@ -101,6 +101,14 @@
               type=str,
               default="http://mlflow:5000",
               help=("The MLflow tracking URI to connect to the tracking backend."))
+@click.option('--mlflow_experiment_name_template',
+              type=str,
+              default="dfp/{source}/training/{reg_model_name}",
+              help="The MLflow experiment name template to use when logging experiments. ")
+@click.option('--mlflow_model_name_template',
+              type=str,
+              default="DFP-{source}-{user_id}",
+              help="The MLflow model name template to use when logging models. ")
 @click.option('--bootstrap_servers',
               type=str,
               default="localhost:9092",
@@ -138,6 +146,8 @@ def run_pipeline(source: str,
                  tracking_uri,
                  silence_monitors,
                  use_cpp,
+                 mlflow_experiment_name_template,
+                 mlflow_model_name_template,
                  **kwargs):
     if (skip_user and only_user):
         logging.error("Option --skip_user and --only_user are mutually exclusive. Exiting")
@@ -152,6 +162,8 @@ def run_pipeline(source: str,
                                   source,
                                   tracking_uri,
                                   silence_monitors,
+                                  mlflow_experiment_name_template,
+                                  mlflow_model_name_template,
                                   train_users)
 
     dfp_arg_parser.init()

morpheus/controllers/mlflow_model_writer_controller.py

@@ -86,6 +86,27 @@ def experiment_name_formatter(self):
     def databricks_permissions(self):
         return self._databricks_permissions
 
+    def _create_safe_user_id(self, user_id: str):
+        """
+        Creates a safe user ID for use in MLflow model names and experiment names.
+
+        Parameters
+        ----------
+        user_id : str
+            The user ID.
+
+        Returns
+        -------
+        str
+            The generated safe user ID.
+        """
+
+        safe_user_id = user_id.replace('.', '_dot_')
+        safe_user_id = safe_user_id.replace('/', '_slash_')
+        safe_user_id = safe_user_id.replace(':', '_colon_')
+
+        return safe_user_id
+
     def user_id_to_model(self, user_id: str):
         """
         Converts a user ID to an model name
@@ -102,7 +123,7 @@ def user_id_to_model(self, user_id: str):
         """
 
         kwargs = {
-            "user_id": user_id,
+            "user_id": self._create_safe_user_id(user_id),
             "user_md5": hashlib.md5(user_id.encode('utf-8')).hexdigest(),
         }
 
@@ -123,9 +144,11 @@ def user_id_to_experiment(self, user_id: str) -> str:
             The generated experiment name.
         """
 
+        safe_user_id = self._create_safe_user_id(user_id)
+
         kwargs = {
-            "user_id": user_id,
-            "user_md5": hashlib.md5(user_id.encode('utf-8')).hexdigest(),
+            "user_id": safe_user_id,
+            "user_md5": hashlib.md5(safe_user_id.encode('utf-8')).hexdigest(),
             "reg_model_name": self.user_id_to_model(user_id=user_id)
         }