Add two methods to facilitate navigation from saved model's objects to analysis' objects:

- for getting the mltask from a saved model
- for getting the trained model from a saved model version

Author: Louis Pouillot

dataikuapi/dss/ml.py

@@ -1,3 +1,4 @@
+from dataikuapi.dss.utils import extract_info_from_full_model_id
 from ..utils import DataikuException
 from ..utils import DataikuUTF8CSVReader
 from ..utils import DataikuStreamedHttpUTF8CSVReader
@@ -524,6 +525,23 @@ def save_user_meta(self):
                 "PUT", "/projects/%s/savedmodels/%s/versions/%s/user-meta" % (self.saved_model.project_key,
                     self.saved_model.sm_id, self.saved_model_version), body = um)
 
+    def get_origin_analysis_trained_model(self):
+        """
+        Fetch details about the model in an analysis, this model has been exported from
+
+        :rtype: DSSTrainedModelDetails
+        """
+        if self.saved_model is None:
+            return self
+        else:
+            if "smOrigin" not in self.get_raw():
+                raise DataikuException("Unknow ")
+            fmi = self.get_raw()["smOrigin"]["fullModelId"]
+            _, analysis_id, mltask_id = extract_info_from_full_model_id(fmi)
+
+            origin_ml_task = DSSMLTask(self.saved_model.client, self.saved_model.project_key, analysis_id, mltask_id)
+            return origin_ml_task.get_trained_model_details(fmi)
+
 class DSSTreeNode(object):
     def __init__(self, tree, i):
         self.tree = tree

dataikuapi/dss/savedmodel.py

@@ -1,3 +1,5 @@
+from dataikuapi.dss.ml import DSSMLTask
+from dataikuapi.dss.utils import extract_info_from_full_model_id
 from .ml import DSSTrainedPredictionModelDetails, DSSTrainedClusteringModelDetails
 from .metrics import ComputedMetrics
 from .ml import DSSTrainedClusteringModelDetails
@@ -15,6 +17,9 @@ def __init__(self, client, project_key, sm_id):
         self.project_key = project_key
         self.sm_id = sm_id
 
+    def get_definition(self):
+        return self.client._perform_json(
+            "GET", "/projects/%s/savedmodels/%s" % (self.project_key, self.sm_id))
 
     ########################################################
     # Versions
@@ -86,6 +91,18 @@ def delete_versions(self, versions, remove_intermediate=True):
         self.client._perform_empty(
             "POST", "/projects/%s/savedmodels/%s/actions/delete-versions" % (self.project_key, self.sm_id),
             body=body)
+
+    def get_origin_ml_task(self):
+        """
+        Fetch the last ML task that has been exported to this saved model
+
+        :rtype: DSSMLTask
+        """
+        definition = self.get_definition()
+        fmi = definition["lastExportedFrom"]
+        _, analysis_id, ml_task_id = extract_info_from_full_model_id(fmi)
+        return DSSMLTask(self.client, self.project_key, analysis_id, ml_task_id)
+
     ########################################################
     # Metrics
     ########################################################

dataikuapi/dss/utils.py

@@ -1,3 +1,6 @@
+import re
+
+
 class DSSDatasetSelectionBuilder(object):
     """Builder for a "dataset selection". In DSS, a dataset selection is used to select a part of a dataset for processing.
 
@@ -257,4 +260,9 @@ def custom_fields(self):
 
     @custom_fields.setter
     def custom_fields(self, custom_fields):
-        self._tod["customFields"] = custom_fields
+        self._tod["customFields"] = custom_fields
+
+
+def extract_info_from_full_model_id(full_model_id):
+    match = re.search(u'([\w]+)-([\w]+)-([\w]+)-s\w+-pp\w+-m\w+', full_model_id)
+    return match.group(1), match.group(2), match.group(3)