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| """Profiler utilities.""" |
|
|
| import collections |
| import contextlib |
| import datetime |
| import time |
| import numpy as np |
|
|
|
|
| class SmoothedValue(object): |
| """Track values and provide smoothed report.""" |
|
|
| def __init__(self, window_size=None, fmt=None): |
| self.fmt = fmt or "{median:.4f} ({mean:.4f})" |
| self.deque = collections.deque(maxlen=window_size) |
|
|
| def __str__(self): |
| return self.fmt.format(value=self.value, mean=self.mean, median=self.median) |
|
|
| @property |
| def value(self): |
| return self.deque[-1] |
|
|
| @property |
| def mean(self): |
| return np.mean(self.deque) |
|
|
| @property |
| def median(self): |
| return np.median(self.deque) |
|
|
| def update(self, value): |
| self.deque.append(value) |
|
|
|
|
| class Timer(object): |
| """Simple timer.""" |
|
|
| def __init__(self): |
| self.total_time = 0.0 |
| self.calls = 0 |
| self.start_time = 0.0 |
| self.diff = 0.0 |
| self.average_time = 0.0 |
|
|
| def add_diff(self, diff, n=1, average=False): |
| self.total_time += diff |
| self.calls += n |
| self.average_time = self.total_time / self.calls |
| return self.average_time if average else self.diff |
|
|
| @contextlib.contextmanager |
| def tic_and_toc(self, n=1): |
| try: |
| yield self.tic() |
| finally: |
| self.toc(n) |
|
|
| def tic(self): |
| self.start_time = time.time() |
| return self |
|
|
| def toc(self, n=1, average=False): |
| self.diff = time.time() - self.start_time |
| return self.add_diff(self.diff, n, average) |
|
|
|
|
| def get_progress(timer, step, max_steps): |
| """Return the progress information.""" |
| eta_seconds = timer.average_time * (max_steps - step) |
| eta = str(datetime.timedelta(seconds=int(eta_seconds))) |
| progress = (step + 1.0) / max_steps |
| return "< PROGRESS: {:.2%} | SPEED: {:.3f}s / step | ETA: {} >".format( |
| progress, timer.average_time, eta |
| ) |
|
|
