Refactor benchmark object, benchmarker, and introduce aggregators as reducer patterns for working with the new scheduler refactor

Author: markurtz

src/guidellm/backend/backend.py

@@ -109,8 +109,8 @@ def requests_limit(self) -> Optional[int]:
     @abstractmethod
     def info(self) -> dict[str, Any]:
         """
-        :return: Backend metadata including model information, endpoints, and
-            configuration data for reporting and diagnostics.
+        :return: Backend metadata including model any initializaiton and
+            configuration information.
         """
         ...
 

src/guidellm/backend/objects.py

@@ -92,6 +92,48 @@ class GenerationResponse(StandardBaseModel):
         default=None, description="Actual output token count reported by the backend."
     )
 
+    @property
+    def prompt_tokens(self) -> Optional[int]:
+        """
+        :return: The number of prompt tokens used in the request
+            (response_prompt_tokens if available, otherwise request_prompt_tokens).
+        """
+        return self.response_prompt_tokens or self.request_prompt_tokens
+
+    @property
+    def output_tokens(self) -> Optional[int]:
+        """
+        :return: The number of output tokens generated in the response
+            (response_output_tokens if available, otherwise request_output_tokens).
+        """
+        return self.response_output_tokens or self.request_output_tokens
+
+    @property
+    def total_tokens(self) -> Optional[int]:
+        """
+        :return: The total number of tokens used in the request and response.
+            Sum of prompt_tokens and output_tokens.
+        """
+        if self.prompt_tokens is None or self.output_tokens is None:
+            return None
+        return self.prompt_tokens + self.output_tokens
+
+    def preferred_prompt_tokens(
+        self, preferred_source: Literal["request", "response"]
+    ) -> Optional[int]:
+        if preferred_source == "request":
+            return self.request_prompt_tokens or self.response_prompt_tokens
+        else:
+            return self.response_prompt_tokens or self.request_prompt_tokens
+
+    def preferred_output_tokens(
+        self, preferred_source: Literal["request", "response"]
+    ) -> Optional[int]:
+        if preferred_source == "request":
+            return self.request_output_tokens or self.response_output_tokens
+        else:
+            return self.response_output_tokens or self.request_output_tokens
+
 
 class GenerationRequestTimings(RequestTimings):
     """Timing model for tracking generation request lifecycle events."""

src/guidellm/benchmark/__init__.py

@@ -3,12 +3,12 @@
     Benchmark,
     BenchmarkArgs,
     BenchmarkMetrics,
-    BenchmarkRunStats,
+    BenchmarkSchedulerStats,
     BenchmarkT,
     GenerativeBenchmark,
     GenerativeMetrics,
+    GenerativeRequestStats,
     GenerativeTextErrorStats,
-    GenerativeTextResponseStats,
     StatusBreakdown,
 )
 from .benchmarker import Benchmarker, BenchmarkerResult, GenerativeBenchmarker
@@ -38,7 +38,7 @@
     "BenchmarkAggregator",
     "BenchmarkArgs",
     "BenchmarkMetrics",
-    "BenchmarkRunStats",
+    "BenchmarkSchedulerStats",
     "BenchmarkT",
     "Benchmarker",
     "BenchmarkerProgressDisplay",
@@ -51,10 +51,10 @@
     "GenerativeBenchmarksConsole",
     "GenerativeBenchmarksReport",
     "GenerativeMetrics",
+    "GenerativeRequestStats",
     "GenerativeTextBenchmarkerProgressDisplay",
     "GenerativeTextBenchmarkerTaskProgressState",
     "GenerativeTextErrorStats",
-    "GenerativeTextResponseStats",
     "Profile",
     "ProfileType",
     "StatusBreakdown",