73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
import time
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class _Timer:
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"""A running stat for conveniently logging the duration of a code block.
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Example:
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wait_timer = TimerStat()
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with wait_timer:
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ray.wait(...)
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Note that this class is *not* thread-safe.
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"""
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def __init__(self, window_size: int = 10):
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"""Initialize a ``_Timer``.
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Args:
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window_size: Number of most recent samples (and per-call units
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processed) to retain when computing the rolling ``mean`` and
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``mean_throughput`` statistics.
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"""
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self._window_size = window_size
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self._samples = []
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self._units_processed = []
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self._start_time = None
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self._total_time = 0.0
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self.count = 0
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def __enter__(self):
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assert self._start_time is None, "concurrent updates not supported"
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self._start_time = time.time()
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def __exit__(self, exc_type, exc_value, tb):
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assert self._start_time is not None
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time_delta = time.time() - self._start_time
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self.push(time_delta)
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self._start_time = None
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def push(self, time_delta):
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self._samples.append(time_delta)
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if len(self._samples) > self._window_size:
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self._samples.pop(0)
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self.count += 1
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self._total_time += time_delta
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def push_units_processed(self, n):
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self._units_processed.append(n)
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if len(self._units_processed) > self._window_size:
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self._units_processed.pop(0)
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def has_units_processed(self):
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return len(self._units_processed) > 0
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@property
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def mean(self):
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if len(self._samples) == 0:
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return 0.0
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return float(sum(self._samples)) / len(self._samples)
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@property
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def mean_units_processed(self):
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if len(self._units_processed) == 0:
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return 0.0
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return float(sum(self._units_processed)) / len(self._units_processed)
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@property
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def mean_throughput(self):
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time_total = float(sum(self._samples))
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if not time_total:
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return 0.0
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return float(sum(self._units_processed)) / time_total
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