Add summary metrics to saved json file (#46)

At the end of the run GuideLLM will print summary metrics that are
computed from the raw results, but these are not currently saved
anywhere.

This PR adds these metrics as serializable properties of the
`TextGenerationBenchmark` class. Most of the metrics are already
declared as properties, but are not serializable. Adding the
`@computed_field` decorator is enough in these cases. Other properties
were added to complete the list.

Author: anmarques

src/guidellm/core/report.py

@@ -147,19 +147,15 @@ def _create_benchmark_report_data_tokens_summary(
     for benchmark in report.benchmarks_sorted:
         table.add_row(
             _benchmark_rate_id(benchmark),
-            f"{benchmark.prompt_token_distribution.mean:.2f}",
+            f"{benchmark.prompt_token:.2f}",
             ", ".join(
                 f"{percentile:.1f}"
-                for percentile in benchmark.prompt_token_distribution.percentiles(
-                    [1, 5, 50, 95, 99]
-                )
+                for percentile in benchmark.prompt_token_percentiles
             ),
-            f"{benchmark.output_token_distribution.mean:.2f}",
+            f"{benchmark.output_token:.2f}",
             ", ".join(
                 f"{percentile:.1f}"
-                for percentile in benchmark.output_token_distribution.percentiles(
-                    [1, 5, 50, 95, 99]
-                )
+                for percentile in benchmark.output_token_percentiles
             ),
         )
     logger.debug("Created data tokens summary table for the report.")
@@ -181,7 +177,7 @@ def _create_benchmark_report_dist_perf_summary(
         "Benchmark",
         "Request Latency [1%, 5%, 10%, 50%, 90%, 95%, 99%] (sec)",
         "Time to First Token [1%, 5%, 10%, 50%, 90%, 95%, 99%] (ms)",
-        "Inter Token Latency [1%, 5%, 10%, 50%, 90% 95%, 99%] (ms)",
+        "Inter Token Latency [1%, 5%, 10%, 50%, 90%, 95%, 99%] (ms)",
         title="[magenta]Performance Stats by Benchmark[/magenta]",
         title_style="bold",
         title_justify="left",
@@ -193,21 +189,15 @@ def _create_benchmark_report_dist_perf_summary(
             _benchmark_rate_id(benchmark),
             ", ".join(
                 f"{percentile:.2f}"
-                for percentile in benchmark.request_latency_distribution.percentiles(
-                    [1, 5, 10, 50, 90, 95, 99]
-                )
+                for percentile in benchmark.request_latency_percentiles
             ),
             ", ".join(
                 f"{percentile * 1000:.1f}"
-                for percentile in benchmark.ttft_distribution.percentiles(
-                    [1, 5, 10, 50, 90, 95, 99]
-                )
+                for percentile in benchmark.time_to_first_token_percentiles
             ),
             ", ".join(
                 f"{percentile * 1000:.1f}"
-                for percentile in benchmark.itl_distribution.percentiles(
-                    [1, 5, 10, 50, 90, 95, 99]
-                )
+                for percentile in benchmark.inter_token_latency_percentiles
             ),
         )
     logger.debug("Created distribution performance summary table for the report.")

src/guidellm/core/result.py

@@ -2,7 +2,7 @@
 from typing import Any, Dict, List, Literal, Optional, Union
 
 from loguru import logger
-from pydantic import Field
+from pydantic import Field, computed_field
 
 from guidellm.core.distribution import Distribution
 from guidellm.core.request import TextGenerationRequest
@@ -221,6 +221,7 @@ def __iter__(self):
         """
         return iter(self.results)
 
+    @computed_field # type: ignore[misc]
     @property
     def request_count(self) -> int:
         """
@@ -231,6 +232,7 @@ def request_count(self) -> int:
         """
         return len(self.results)
 
+    @computed_field # type: ignore[misc]
     @property
     def error_count(self) -> int:
         """
@@ -241,6 +243,7 @@ def error_count(self) -> int:
         """
         return len(self.errors)
 
+    @computed_field # type: ignore[misc]
     @property
     def total_count(self) -> int:
         """
@@ -251,6 +254,7 @@ def total_count(self) -> int:
         """
         return self.request_count + self.error_count
 
+    @computed_field # type: ignore[misc]
     @property
     def start_time(self) -> Optional[float]:
         """
@@ -264,6 +268,7 @@ def start_time(self) -> Optional[float]:
 
         return self.results[0].start_time
 
+    @computed_field # type: ignore[misc]
     @property
     def end_time(self) -> Optional[float]:
         """
@@ -277,6 +282,7 @@ def end_time(self) -> Optional[float]:
 
         return self.results[-1].end_time
 
+    @computed_field # type: ignore[misc]
     @property
     def duration(self) -> float:
         """
@@ -290,6 +296,7 @@ def duration(self) -> float:
 
         return self.end_time - self.start_time
 
+    @computed_field # type: ignore[misc]
     @property
     def completed_request_rate(self) -> float:
         """
@@ -303,6 +310,7 @@ def completed_request_rate(self) -> float:
 
         return len(self.results) / self.duration
 
+    @computed_field # type: ignore[misc]
     @property
     def request_latency(self) -> float:
         """
@@ -332,6 +340,19 @@ def request_latency_distribution(self) -> Distribution:
             ]
         )
 
+    @computed_field # type: ignore[misc]
+    @property
+    def request_latency_percentiles(self) -> List[float]:
+        """
+        Get standard percentiles of request latency in seconds.
+
+        :return: List of percentile request latency in seconds
+        :rtype: List[float]
+        """
+        return self.request_latency_distribution.percentiles([1, 5, 10, 50, 90, 95, 99])
+
+
+    @computed_field # type: ignore[misc]
     @property
     def time_to_first_token(self) -> float:
         """
@@ -361,6 +382,20 @@ def ttft_distribution(self) -> Distribution:
             ]
         )
 
+    @computed_field # type: ignore[misc]
+    @property
+    def time_to_first_token_percentiles(self) -> List[float]:
+        """
+        Get standard percentiles for time taken to decode the first token
+        in milliseconds.
+
+        :return: List of percentile time taken to decode the first token
+        in milliseconds.
+        :rtype: List[float]
+        """
+        return self.ttft_distribution.percentiles([1, 5, 10, 50, 90, 95, 99])
+
+    @computed_field # type: ignore[misc]
     @property
     def inter_token_latency(self) -> float:
         """
@@ -388,6 +423,18 @@ def itl_distribution(self) -> Distribution:
             ]
         )
 
+    @computed_field # type: ignore[misc]
+    @property
+    def inter_token_latency_percentiles(self) -> List[float]:
+        """
+        Get standard percentiles for the time between tokens in milliseconds.
+
+        :return: List of percentiles for the average time between tokens.
+        :rtype: List[float]
+        """
+        return self.itl_distribution.percentiles([1, 5, 10, 50, 90, 95, 99])
+
+    @computed_field # type: ignore[misc]
     @property
     def output_token_throughput(self) -> float:
         """
@@ -403,6 +450,17 @@ def output_token_throughput(self) -> float:
 
         return total_tokens / self.duration
 
+    @computed_field # type: ignore[misc]
+    @property
+    def prompt_token(self) -> float:
+        """
+        Get the average number of prompt tokens.
+
+        :return: The average number of prompt tokens.
+        :rtype: float
+        """
+        return self.prompt_token_distribution.mean
+
     @property
     def prompt_token_distribution(self) -> Distribution:
         """
@@ -413,6 +471,28 @@ def prompt_token_distribution(self) -> Distribution:
         """
         return Distribution(data=[result.prompt_token_count for result in self.results])
 
+    @computed_field # type: ignore[misc]
+    @property
+    def prompt_token_percentiles(self) -> List[float]:
+        """
+        Get standard percentiles for number of prompt tokens.
+
+        :return: List of percentiles of number of prompt tokens.
+        :rtype: List[float]
+        """
+        return self.prompt_token_distribution.percentiles([1, 5, 50, 95, 99])
+
+    @computed_field # type: ignore[misc]
+    @property
+    def output_token(self) -> float:
+        """
+        Get the average number of output tokens.
+
+        :return: The average number of output tokens.
+        :rtype: float
+        """
+        return self.output_token_distribution.mean
+
     @property
     def output_token_distribution(self) -> Distribution:
         """
@@ -423,6 +503,18 @@ def output_token_distribution(self) -> Distribution:
         """
         return Distribution(data=[result.output_token_count for result in self.results])
 
+    @computed_field # type: ignore[misc]
+    @property
+    def output_token_percentiles(self) -> List[float]:
+        """
+        Get standard percentiles for number of output tokens.
+
+        :return: List of percentiles of number of output tokens.
+        :rtype: List[float]
+        """
+        return self.output_token_distribution.percentiles([1, 5, 50, 95, 99])
+
+    @computed_field # type: ignore[misc]
     @property
     def overloaded(self) -> bool:
         if (