feat: Add unique sequence number for aggregation into supervisor

analytics/tools/aggregate_runs/core_aggregation.py

@@ -3,7 +3,6 @@
 from pathlib import Path
 
 import pandas as pd
-
 from analytics.app.data.transform import dfs_models_and_evals, logs_dataframe
 from analytics.tools.aggregate_runs.dir_utils import load_multiple_logfiles
 from analytics.tools.aggregate_runs.pipeline_equivalence import assert_pipeline_equivalence

modyn/supervisor/internal/pipeline_executor/evaluation_executor.py

@@ -203,6 +203,7 @@ def run_post_pipeline_evaluations(self, eval_status_queue: Queue, manual_run: bo
             # our current process is in terms of position in the dataset.
             parent_log=StageLog(
                 id=PipelineStage.EVALUATE_SINGLE.name,
+                id_seq_num=-1,
                 start=datetime.datetime.now(),
                 batch_idx=-1,
                 sample_idx=-1,
@@ -238,6 +239,7 @@ def _launch_evaluations_async(
         def worker_func(eval_req: EvalRequest) -> StageLog:
             single_log = StageLog(
                 id=PipelineStage.EVALUATE_SINGLE.name,
+                id_seq_num=-1,  # evaluation don't need sequence numbers, their order is not important
                 start=datetime.datetime.now(),
                 batch_idx=parent_log.batch_idx,
                 sample_idx=parent_log.sample_idx,

modyn/supervisor/internal/pipeline_executor/models.py

@@ -104,6 +104,12 @@ class ExecutionState(PipelineExecutionParams):
     stage: PipelineStage = PipelineStage.INIT
     """The current stage of the pipeline executor."""
 
+    stage_id_seq_counters: dict[str, int] = dataclasses.field(default_factory=dict)
+    """Tracks for every stage that can be logged in StageLog how many logs have been created using this id.
+    This information can be used to uniquely identify logs over multiple pipeline runs given the pipelines use
+    a deterministic configuration.
+    """
+
     # for logging
     seen_pipeline_stages: set[PipelineStage] = dataclasses.field(default_factory=set)
     current_batch_index: int = 0
@@ -385,6 +391,10 @@ class StageLog(BaseModel):
     id: str
     """Identifier for the pipeline stage, PipelineStage.name in most cases"""
 
+    id_seq_num: int
+    """Identifies the log within the group of logs with the same id (given by PipelineStage). Used for aggregation over
+    multiple pipeline runs."""
+
     # experiment time
     start: datetime.datetime
     end: datetime.datetime | None = Field(None)

modyn/supervisor/internal/pipeline_executor/pipeline_executor.py

@@ -136,9 +136,12 @@ def report_results(stage_log: StageLog) -> None:
                 logger.info(f"[pipeline {state.pipeline_id}] Entering <{stage}>.")
 
             # execute stage
+            stage_seq_num = state.stage_id_seq_counters.get(stage.name, 0)
+            state.stage_id_seq_counters[stage.name] = stage_seq_num + 1
             epoch_micros_start = current_time_micros()
             stage_log = StageLog(
                 id=stage.name,
+                id_seq_num=stage_seq_num,
                 start=datetime.now(),
                 batch_idx=state.current_batch_index,
                 sample_idx=state.current_sample_index,

modyn/tests/supervisor/internal/pipeline_executor/test_evaluation_executor.py

@@ -132,6 +132,7 @@ def dummy_eval_request() -> EvalRequest:
 def dummy_stage_log() -> StageLog:
     return StageLog(
         id="log",
+        id_seq_num=-1,
         start=datetime.datetime(2021, 1, 1),
         batch_idx=-1,
         sample_idx=-1,
@@ -240,6 +241,7 @@ def test_single_evaluation(
 
     stage_log = StageLog(
         id="log",
+        id_seq_num=-1,
         start=datetime.datetime(2021, 1, 1),
         batch_idx=-1,
         sample_idx=-1,

modyn/tests/supervisor/internal/pipeline_executor/test_pipeline_executor.py

@@ -98,7 +98,7 @@ def dummy_logs(dummy_pipeline_args: PipelineExecutionParams) -> PipelineLogs:
 
 @pytest.fixture
 def dummy_stage_log() -> StageLog:
-    return StageLog(id="dummy", start=0, sample_idx=1, sample_time=1000, trigger_idx=0)
+    return StageLog(id="dummy", id_seq_num=-1, start=0, sample_idx=1, sample_time=1000, trigger_idx=0)
 
 
 @overload