mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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107 lines
4.5 KiB
Python
107 lines
4.5 KiB
Python
"""Utilities for Prometheus Metrics Collection."""
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import time
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from typing import Dict, Optional, Union
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from .enums import MetricNames
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# Adapted from https://github.com/vllm-project/vllm/blob/v0.10.0rc1/vllm/engine/metrics.py#L30
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class MetricsCollector:
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labelname_finish_reason = "finished_reason"
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def __init__(self, labels: Dict[str, str]) -> None:
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from prometheus_client import Counter, Histogram
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self.last_log_time = time.time()
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self.labels = labels
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self.metric_prefix = "trtllm_"
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self.finish_reason_label = {
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MetricsCollector.labelname_finish_reason: "unknown"
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}
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self.labels_with_finished_reason = {
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**self.labels,
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**self.finish_reason_label
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}
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self.counter_request_success = Counter(
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name=self.metric_prefix + "request_success_total",
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documentation="Count of successfully processed requests.",
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labelnames=self.labels_with_finished_reason.keys())
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self.histogram_e2e_time_request = Histogram(
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name=self.metric_prefix + "e2e_request_latency_seconds",
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documentation="Histogram of end to end request latency in seconds.",
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buckets=[
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0.3, 0.5, 0.8, 1.0, 1.5, 2.0, 2.5, 5.0, 10.0, 15.0, 20.0, 30.0,
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40.0, 50.0, 60.0, 120.0, 240.0, 480.0, 960.0, 1920.0, 7680.0
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],
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labelnames=self.labels.keys())
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self.histogram_time_to_first_token = Histogram(
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name=self.metric_prefix + "time_to_first_token_seconds",
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documentation="Histogram of time to first token in seconds.",
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buckets=[
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0.001, 0.005, 0.01, 0.02, 0.04, 0.06, 0.08, 0.1, 0.25, 0.5,
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0.75, 1.0, 2.5, 5.0, 7.5, 10.0, 20.0, 40.0, 80.0, 160.0, 640.0,
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2560.0
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],
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labelnames=self.labels.keys())
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self.histogram_time_per_output_token = Histogram(
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name=self.metric_prefix + "time_per_output_token_seconds",
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documentation="Histogram of time per output token in seconds.",
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buckets=[
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0.01, 0.025, 0.05, 0.075, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 0.75,
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1.0, 2.5, 5.0, 7.5, 10.0, 20.0, 40.0, 80.0
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],
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labelnames=self.labels.keys())
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self.histogram_queue_time_request = Histogram(
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name=self.metric_prefix + "request_queue_time_seconds",
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documentation=
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"Histogram of time spent in WAITING phase for request.",
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buckets=[
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0.3, 0.5, 0.8, 1.0, 1.5, 2.0, 2.5, 5.0, 10.0, 15.0, 20.0, 30.0,
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40.0, 50.0, 60.0, 120.0, 240.0, 480.0, 960.0, 1920.0, 7680.0
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],
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labelnames=self.labels.keys())
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def _label_merge(self, labels: Dict[str, str]) -> Dict[str, str]:
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if labels is None or len(labels) == 0:
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return self.labels
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return {**self.labels, **labels}
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def _log_counter(self, counter, labels: Dict[str, str],
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data: Union[int, float]) -> None:
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# Convenience function for logging to counter.
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counter.labels(**self._label_merge(labels)).inc(data)
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def _log_histogram(self, histogram, data: Union[int, float]) -> None:
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# Convenience function for logging to histogram.
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histogram.labels(**self.labels).observe(data)
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def log_request_success(self, data: Union[int, float],
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labels: Dict[str, str]) -> None:
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self._log_counter(self.counter_request_success, labels, data)
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self.last_log_time = time.time()
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def log_histogram(self, data: Optional[dict[str, float]]) -> None:
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if e2e := data.get(MetricNames.E2E, 0):
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self._log_histogram(self.histogram_e2e_time_request, e2e)
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if ttft := data.get(MetricNames.TTFT, 0):
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self._log_histogram(self.histogram_time_to_first_token, ttft)
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if tpot := data.get(MetricNames.TPOT, 0):
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self._log_histogram(self.histogram_time_per_output_token, tpot)
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if request_queue_time := data.get(MetricNames.REQUEST_QUEUE_TIME, 0):
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self._log_histogram(self.histogram_queue_time_request,
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request_queue_time)
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self.last_log_time = time.time()
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def log_metrics_dict(self, metrics_dict: dict[str, float]) -> None:
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if finish_reason := metrics_dict.get(
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MetricsCollector.labelname_finish_reason):
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self.log_request_success(
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1, {MetricsCollector.labelname_finish_reason: finish_reason})
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self.log_histogram(metrics_dict)
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