Turn statistics into GAP Records

genai-perf/genai_perf/measurements/model_config_measurement.py

@@ -20,6 +20,7 @@
 from typing import Any, Dict, Optional, TypeAlias
 
 from genai_perf.record.record import Record
+from genai_perf.record.types.request_throughput_avg import RequestThroughputAvg
 from genai_perf.types import (
     CheckpointObject,
     MetricObjectives,
@@ -39,7 +40,7 @@
 ###########################################################################
 @dataclass(frozen=True)
 class ModelConfigMeasurementDefaults:
-    METRIC_OBJECTIVE = {"perf_throughput": 1.0}
+    METRIC_OBJECTIVE = {RequestThroughputAvg.tag: 1.0}
 
     SELF_IS_BETTER = 1
     OTHER_IS_BETTER = -1

genai-perf/genai_perf/metrics/statistics.py

@@ -32,8 +32,10 @@
 
 import numpy as np
 import pandas as pd
+from genai_perf.exceptions import GenAIPerfException
 from genai_perf.metrics.metrics import Metrics
 from genai_perf.metrics.telemetry_metrics import TelemetryMetrics
+from genai_perf.record.record import Record, RecordType
 
 
 class Statistics:
@@ -192,3 +194,26 @@
 
         filepath = artifact_dir / f"{filename}.gzip"
         df.to_parquet(filepath, compression="gzip")
+
+    def create_records(self) -> List[Record]:
+        """
+        Populates and returns a list of Records
+        """
+        statistic_records = []
+        for metric_base_name, metric_info in self.stats_dict.items():
+            for metric_post_name, metric_value in metric_info.items():
+                if metric_post_name == "unit":
+                    continue
+
+                metric_name = metric_base_name + "_" + metric_post_name
+
+                try:
+                    new_record = RecordType.get_all_record_types()[metric_name](
+                        metric_value
+                    )
+                except KeyError:
+                    GenAIPerfException(f"{metric_name} is not a valid Record tag.")
+
+                statistic_records.append(new_record)
+
+        return statistic_records

genai-perf/genai_perf/record/record.py

@@ -19,6 +19,7 @@
 from typing import Dict, Union
 
 from genai_perf.exceptions import GenAIPerfException
+from genai_perf.types import RecordValue
 
 
 class RecordType(ABCMeta):
@@ -90,16 +91,7 @@ class Record(metaclass=RecordType):
     records
     """
 
-    def __init__(self, value: Union[float, int], timestamp: int):
-        """
-        Parameters
-        ----------
-        value : float or int
-            The value of the GPU metric
-        timestamp : int
-            The timestamp for the record in nanoseconds
-        """
-
+    def __init__(self, value: RecordValue, timestamp: int):
         assert type(value) is float or type(value) is int
         assert type(timestamp) is int
 
@@ -124,16 +116,12 @@ def aggregation_function():
     def value_function() -> float:
         """
         Returns the average value from a list
-
-        Returns
-        -------
-        Average value of the list
         """
         return mean  # type: ignore
 
     @staticmethod
     @abstractmethod
-    def header(aggregation_tag=False):
+    def header(aggregation_tag=False) -> str:
         """
         Parameters
         ----------
@@ -170,7 +158,7 @@ def create_class_from_checkpoint(cls, record_dict) -> "Record":
                 setattr(record, key, record_dict[key])
         return record
 
-    def value(self) -> Union[float, int]:
+    def value(self) -> RecordValue:
         """
         This method returns the value of recorded metric
 

genai-perf/genai_perf/record/types/gpu_energy_consumption.py

@@ -0,0 +1,56 @@
+# Copyright 2021-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from functools import total_ordering
+
+from genai_perf.record.gpu_record import DecreasingGPURecord
+
+
+@total_ordering
+class GPUEnergyConsumption(DecreasingGPURecord):
+    """
+    GPU's energy consumption metric
+    """
+
+    tag = "energy_consumption"
+
+    def __init__(self, value, device_uuid=None, timestamp=0):
+        super().__init__(value, device_uuid, timestamp)
+
+    @staticmethod
+    def aggregation_function():
+        def average(seq):
+            return sum(seq[1:], start=seq[0]) / len(seq)
+
+        return average
+
+    @staticmethod
+    def header(aggregation_tag=False):
+        return ("Average " if aggregation_tag else "") + "GPU Energy Consumption (MJ)"
+
+    def __eq__(self, other: "GPUEnegryConsumption") -> bool:  # type: ignore
+        return self.value() == other.value()
+
+    def __lt__(self, other: "GPUEnergyConsumption") -> bool:
+        return other.value() < self.value()
+
+    def __add__(self, other: "GPUEnergyConsumption") -> "GPUEnergyConsumption":
+        return GPUEnergyConsumption(
+            device_uuid=None, value=(self.value() + other.value())
+        )
+
+    def __sub__(self, other: "GPUEnergyConsumption") -> "GPUEnergyConsumption":
+        return GPUEnergyConsumption(
+            device_uuid=None, value=(other.value() - self.value())
+        )