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from time import perf_counter as timer |
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from collections import OrderedDict |
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import numpy as np |
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class Profiler: |
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def __init__(self, summarize_every=5, disabled=False): |
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self.last_tick = timer() |
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self.logs = OrderedDict() |
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self.summarize_every = summarize_every |
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self.disabled = disabled |
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def tick(self, name): |
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if self.disabled: |
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return |
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if not name in self.logs: |
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self.logs[name] = [] |
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if len(self.logs[name]) >= self.summarize_every: |
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self.summarize() |
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self.purge_logs() |
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self.logs[name].append(timer() - self.last_tick) |
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self.reset_timer() |
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def purge_logs(self): |
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for name in self.logs: |
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self.logs[name].clear() |
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def reset_timer(self): |
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self.last_tick = timer() |
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def summarize(self): |
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n = max(map(len, self.logs.values())) |
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assert n == self.summarize_every |
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print("\nAverage execution time over %d steps:" % n) |
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name_msgs = ["%s (%d/%d):" % (name, len(deltas), n) for name, deltas in self.logs.items()] |
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pad = max(map(len, name_msgs)) |
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for name_msg, deltas in zip(name_msgs, self.logs.values()): |
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print(" %s mean: %4.0fms std: %4.0fms" % |
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(name_msg.ljust(pad), np.mean(deltas) * 1000, np.std(deltas) * 1000)) |
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print("", flush=True) |
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