[AL-5942] Exports v2 integration tests

tests/integration/annotation_import/test_mea_prediction_import.py

@@ -80,6 +80,7 @@ def test_create_from_objects_all_project_labels(
 def test_model_run_project_labels(model_run_with_all_project_labels,
                                   model_run_predictions):
     model_run = model_run_with_all_project_labels
+    # TODO: Move to export_v2
     model_run_exported_labels = model_run.export_labels(download=True)
     labels_indexed_by_schema_id = {}
     for label in model_run_exported_labels:

tests/integration/annotation_import/test_model_run.py

@@ -7,23 +7,6 @@
 from labelbox import DataSplit, ModelRun
 
 
-def _model_run_export_v2_results(model_run, task_name, params, num_retries=5):
-    """Export model run results and retry if no results are returned."""
-    while (num_retries > 0):
-        task = model_run.export_v2(task_name, params=params)
-        assert task.name == task_name
-        task.wait_till_done()
-        assert task.status == "COMPLETE"
-        assert task.errors is None
-        task_results = task.result
-        if len(task_results) == 0:
-            num_retries -= 1
-            time.sleep(5)
-        else:
-            return task_results
-    return []
-
-
 def test_model_run(client, configured_project_with_label, data_row, rand_gen):
     project, _, _, label = configured_project_with_label
     label_id = label.uid
@@ -182,38 +165,6 @@ def get_model_run_status():
                                                errorMessage)
 
 
-def test_model_run_export_v2(model_run_with_data_rows, configured_project):
-    task_name = "test_task"
-    media_attributes = True
-    params = {"media_attributes": media_attributes, "predictions": True}
-    task_results = _model_run_export_v2_results(model_run_with_data_rows,
-                                                task_name, params)
-    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:
-        # 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['experiments'][
-            model_run_with_data_rows.model_id]['runs'][
-                model_run_with_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
-
-
 def test_model_run_split_assignment_by_data_row_ids(model_run, dataset,
                                                     image_url):
     n_data_rows = 10

tests/integration/conftest.py

@@ -11,7 +11,7 @@
 import requests
 
 from labelbox import Client, MediaType
-from labelbox import LabelingFrontend
+from labelbox import LabelingFrontend, Dataset
 from labelbox import OntologyBuilder, Tool, Option, Classification, MediaType
 from labelbox.orm import query
 from labelbox.pagination import PaginatedCollection
@@ -22,6 +22,7 @@
 from labelbox.schema.user import User
 
 IMG_URL = "https://picsum.photos/200/300.jpg"
+SMALL_DATASET_URL = "https://storage.googleapis.com/lb-artifacts-testing-public/sdk_integration_test/potato.jpeg"
 DATA_ROW_PROCESSING_WAIT_TIMEOUT_SECONDS = 30
 DATA_ROW_PROCESSING_WAIT_SLEEP_INTERNAL_SECONDS = 5
 
@@ -247,6 +248,19 @@ def unique_dataset(client, rand_gen):
     dataset.delete()
 
 
+@pytest.fixture
+def small_dataset(dataset: Dataset):
+    task = dataset.create_data_rows([
+        {
+            "row_data": SMALL_DATASET_URL,
+            "external_id": "my-image"
+        },
+    ] * 2)
+    task.wait_till_done()
+
+    yield dataset
+
+
 @pytest.fixture
 def data_row(dataset, image_url, rand_gen):
     task = dataset.create_data_rows([