Record task start and end times for Acute-Evals

parlai/crowdsourcing/tasks/acute_eval/acute_eval_agent_state.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 
-from typing import List, Dict, Any, TYPE_CHECKING
+from typing import List, Dict, Any, Optional, TYPE_CHECKING
 from mephisto.abstractions.blueprints.abstract.static_task.static_agent_state import (
     StaticAgentState,
 )
@@ -49,3 +49,15 @@ def update_data(self, packet: "Packet") -> None:
         self.state["times"]["task_end"] = time.time()
         self.state["outputs"] = packet.data["task_data"]
         self.save_data()
+
+    def get_task_start(self) -> Optional[float]:
+        """
+        Extract out the start time recorded for this task.
+        """
+        return self.state['times']['task_start']
+
+    def get_task_end(self) -> Optional[float]:
+        """
+        Extract out the end recorded for this task.
+        """
+        return self.state['times']['task_end']

parlai/crowdsourcing/tasks/acute_eval/util.py

@@ -6,7 +6,7 @@
 
 import hashlib
 import os
-from typing import Iterable, List, Tuple, Union
+from typing import Iterable, List, Optional, Tuple, Union
 
 import pandas as pd
 from pytest_regressions.data_regression import DataRegressionFixture
@@ -114,6 +114,7 @@ def test_full_csv(
             results_folder=outputs['results_folder'],
             file_suffix='full.csv',
             dataframe_regression=dataframe_regression,
+            drop_columns=['task_start', 'time_taken'],
         )
 
     def test_grid_csv(
@@ -169,11 +170,21 @@ def _check_dataframe(
         results_folder: str,
         file_suffix: str,
         dataframe_regression: DataFrameRegressionFixture,
+        drop_columns: Optional[list] = None,
     ):
+        """
+        Check a dataframe for correctness.
+
+        Check the dataframe stored at the file with suffix file_suffix in the folder
+        results_folder. Pass in drop_column to indicate columns that shouldn't be
+        checked because they will vary across runs (for instance, timestamp columns).
+        """
+        if drop_columns is None:
+            drop_columns = []
         file_path = self._get_matching_file_path(
             results_folder=results_folder, file_suffix=file_suffix
         )
-        df = pd.read_csv(file_path)
+        df = pd.read_csv(file_path).drop(columns=drop_columns)
         dataframe_regression.check(data_frame=df)
 
     def _check_file_contents(