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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,85 @@ | ||
| # Copyright (C) 2024 Intel Corporation | ||
| # SPDX-License-Identifier: Apache-2.0 | ||
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| import numpy as np | ||
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| # name => statistic dict | ||
| statistics_dict = {} | ||
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| class BaseStatistics: | ||
| """Base class to store in-memory statistics of an entity for measurement in one service.""" | ||
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| def __init__( | ||
| self, | ||
| ): | ||
| self.response_times = [] # store responses time for all requests | ||
| self.first_token_latencies = [] # store first token latencies for all requests | ||
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| def append_latency(self, latency, first_token_latency=None): | ||
| self.response_times.append(latency) | ||
| if first_token_latency: | ||
| self.first_token_latencies.append(first_token_latency) | ||
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| def calcuate_statistics(self): | ||
| if not self.response_times: | ||
| return { | ||
| "p50_latency": None, | ||
| "p99_latency": None, | ||
| "average_latency": None, | ||
| } | ||
| # Calculate the P50 (median) | ||
| p50 = np.percentile(self.response_times, 50) | ||
|
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| # Calculate the P99 | ||
| p99 = np.percentile(self.response_times, 99) | ||
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| avg = np.average(self.response_times) | ||
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| return { | ||
| "p50_latency": p50, | ||
| "p99_latency": p99, | ||
| "average_latency": avg, | ||
| } | ||
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| def calcuate_first_token_statistics(self): | ||
| if not self.first_token_latencies: | ||
| return { | ||
| "p50_latency_first_token": None, | ||
| "p99_latency_first_token": None, | ||
| "average_latency_first_token": None, | ||
| } | ||
| # Calculate the P50 (median) | ||
| p50 = np.percentile(self.first_token_latencies, 50) | ||
|
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| # Calculate the P99 | ||
| p99 = np.percentile(self.first_token_latencies, 99) | ||
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| avg = np.average(self.first_token_latencies) | ||
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| return { | ||
| "p50_latency_first_token": p50, | ||
| "p99_latency_first_token": p99, | ||
| "average_latency_first_token": avg, | ||
| } | ||
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| def register_statistics( | ||
| names, | ||
| ): | ||
| def decorator(func): | ||
| for name in names: | ||
| statistics_dict[name] = BaseStatistics() | ||
| return func | ||
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| return decorator | ||
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| def collect_all_statistics(): | ||
| results = {} | ||
| if statistics_dict: | ||
| for name, statistic in statistics_dict.items(): | ||
| tmp_dict = statistic.calcuate_statistics() | ||
| tmp_dict.update(statistic.calcuate_first_token_statistics()) | ||
| results.update({name: tmp_dict}) | ||
| return results |
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