[AL-4398] Add Model Run exports

labelbox/schema/export_params.py

@@ -0,0 +1,25 @@
+import sys
+
+from typing import Optional
+if sys.version_info >= (3, 8):
+    from typing import TypedDict
+else:
+    from typing_extensions import TypedDict
+
+
+class DataRowParams(TypedDict):
+    data_row_details: Optional[bool]
+    media_attributes: Optional[bool]
+    metadata_fields: Optional[bool]
+    attachments: Optional[bool]
+
+
+class ProjectExportParams(DataRowParams):
+    project_details: Optional[bool]
+    label_details: Optional[bool]
+    performance_details: Optional[bool]
+
+
+class ModelRunExportParams(DataRowParams):
+    # TODO: Add model run fields
+    pass

labelbox/schema/model_run.py

@@ -12,6 +12,9 @@
 from labelbox.orm.query import results_query_part
 from labelbox.orm.model import Field, Relationship, Entity
 from labelbox.orm.db_object import DbObject, experimental
+from labelbox.schema.export_params import ModelRunExportParams
+from labelbox.schema.task import Task
+from labelbox.schema.user import User
 
 if TYPE_CHECKING:
     from labelbox import MEAPredictionImport
@@ -446,6 +449,63 @@ def export_labels(
                          self.uid)
             time.sleep(sleep_time)
 
+    """
+    Creates a model run export task with the given params and returns the task.
+
+    >>>    export_task = export_v2("my_export_task", params={"media_attributes": True})
+
+    """
+
+    def export_v2(self, task_name: str,
+                  params: Optional[ModelRunExportParams]) -> Task:
+        _params = params or {}
+        mutation_name = "exportDataRowsInModelRun"
+        create_task_query_str = """mutation exportDataRowsInModelRunPyApi($input: ExportDataRowsInModelRunInput!){
+          %s(input: $input) {taskId} }
+          """ % (mutation_name)
+        params = {
+            "input": {
+                "taskName": task_name,
+                "filters": {
+                    "modelRunId": self.uid
+                },
+                "params": {
+                    "includeAttachments":
+                        _params.get('attachments', False),
+                    "includeMediaAttributes":
+                        _params.get('media_attributes', False),
+                    "includeMetadata":
+                        _params.get('metadata_fields', False),
+                    "includeDataRowDetails":
+                        _params.get('data_row_details', False),
+                    # Arguments locked based on exectuion context
+                    "includeProjectDetails":
+                        False,
+                    "includeLabels":
+                        False,
+                    "includePerformanceDetails":
+                        False,
+                },
+            }
+        }
+        res = self.client.execute(
+            create_task_query_str,
+            params,
+        )
+        res = res[mutation_name]
+        task_id = res["taskId"]
+        user: User = self.client.get_user()
+        tasks: List[Task] = list(
+            user.created_tasks(where=Entity.Task.uid == task_id))
+        # Cache user in a private variable as the relationship can't be
+        # resolved due to server-side limitations (see Task.created_by)
+        # for more info.
+        if len(tasks) != 1:
+            raise ResourceNotFoundError(Entity.Task, task_id)
+        task: Task = tasks[0]
+        task._user = user
+        return task
+
 
 class ModelRunDataRow(DbObject):
     label_id = Field.String("label_id")

labelbox/schema/task.py

@@ -81,6 +81,9 @@ def wait_till_done(self, timeout_seconds=300) -> None:
     def errors(self) -> Optional[Dict[str, Any]]:
         """ Fetch the error associated with an import task.
         """
+        # TODO: We should handle error messages for export v2 tasks in the future.
+        if self.name != 'JSON Import':
+            return None
         if self.status == "FAILED":
             result = self._fetch_remote_json()
             return result["error"]

tests/integration/annotation_import/test_model_run.py

@@ -1,8 +1,11 @@
+import json
 import time
 import os
 import pytest
 
 from collections import Counter
+
+import requests
 from labelbox import DataSplit, ModelRun
 
 
@@ -114,6 +117,52 @@ def test_model_run_export_labels(model_run_with_model_run_data_rows):
     assert len(labels) == 3
 
 
+def test_model_run_export_v2(model_run_with_model_run_data_rows,
+                             configured_project):
+    task_name = "test_task"
+
+    media_attributes = True
+    params = {"media_attributes": media_attributes}
+    task = model_run_with_model_run_data_rows.export_v2(task_name,
+                                                        params=params)
+    assert task.name == task_name
+    task.wait_till_done()
+    assert task.status == "COMPLETE"
+
+    def download_result(result_url):
+        response = requests.get(result_url)
+        response.raise_for_status()
+        data = [json.loads(line) for line in response.text.splitlines()]
+        return data
+
+    task_results = download_result(task.result_url)
+
+    label_ids = [label.uid for label in configured_project.labels()]
+    label_ids_set = set(label_ids)
+
+    assert len(task_results) == len(label_ids)
+    for task_result in task_results:
+        assert len(task_result['errors']) == 0
+        # Check export param handling
+        if media_attributes:
+            assert 'media_attributes' in task_result and task_result[
+                'media_attributes'] is not None
+        else:
+            assert 'media_attributes' not in task_result or task_result[
+                'media_attributes'] is None
+        model_run = task_result['models'][
+            model_run_with_model_run_data_rows.model_id]['model_runs'][
+                model_run_with_model_run_data_rows.uid]
+        task_label_ids_set = set(
+            map(lambda label: label['id'], model_run['labels']))
+        task_prediction_ids_set = set(
+            map(lambda prediction: prediction['id'], model_run['predictions']))
+        for label_id in task_label_ids_set:
+            assert label_id in label_ids_set
+        for prediction_id in task_prediction_ids_set:
+            assert prediction_id in label_ids_set
+
+
 @pytest.mark.skipif(condition=os.environ['LABELBOX_TEST_ENVIRON'] == "onprem",
                     reason="does not work for onprem")
 def test_model_run_status(model_run_with_model_run_data_rows):