Shortcuts

Source code for mmengine.utils.progressbar

# Copyright (c) OpenMMLab. All rights reserved.
import sys
from collections.abc import Iterable
from multiprocessing import Pool
from shutil import get_terminal_size

from .timer import Timer


[docs]class ProgressBar: """A progress bar which can print the progress.""" def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout): self.task_num = task_num self.bar_width = bar_width self.completed = 0 self.file = file if start: self.start() @property def terminal_width(self): width, _ = get_terminal_size() return width def start(self): if self.task_num > 0: self.file.write(f'[{" " * self.bar_width}] 0/{self.task_num}, ' 'elapsed: 0s, ETA:') else: self.file.write('completed: 0, elapsed: 0s') self.file.flush() self.timer = Timer() def update(self, num_tasks=1): assert num_tasks > 0 self.completed += num_tasks elapsed = self.timer.since_start() if elapsed > 0: fps = self.completed / elapsed else: fps = float('inf') if self.task_num > 0: percentage = self.completed / float(self.task_num) eta = int(elapsed * (1 - percentage) / percentage + 0.5) msg = f'\r[{{}}] {self.completed}/{self.task_num}, ' \ f'{fps:.1f} task/s, elapsed: {int(elapsed + 0.5)}s, ' \ f'ETA: {eta:5}s' bar_width = min(self.bar_width, int(self.terminal_width - len(msg)) + 2, int(self.terminal_width * 0.6)) bar_width = max(2, bar_width) mark_width = int(bar_width * percentage) bar_chars = '>' * mark_width + ' ' * (bar_width - mark_width) self.file.write(msg.format(bar_chars)) else: self.file.write( f'completed: {self.completed}, elapsed: {int(elapsed + 0.5)}s,' f' {fps:.1f} tasks/s') self.file.flush()
[docs]def track_progress(func, tasks, bar_width=50, file=sys.stdout, **kwargs): """Track the progress of tasks execution with a progress bar. Tasks are done with a simple for-loop. Args: func (callable): The function to be applied to each task. tasks (list or tuple[Iterable, int]): A list of tasks or (tasks, total num). bar_width (int): Width of progress bar. Returns: list: The task results. """ if isinstance(tasks, tuple): assert len(tasks) == 2 assert isinstance(tasks[0], Iterable) assert isinstance(tasks[1], int) task_num = tasks[1] tasks = tasks[0] elif isinstance(tasks, Iterable): task_num = len(tasks) else: raise TypeError( '"tasks" must be an iterable object or a (iterator, int) tuple') prog_bar = ProgressBar(task_num, bar_width, file=file) results = [] for task in tasks: results.append(func(task, **kwargs)) prog_bar.update() prog_bar.file.write('\n') return results
def init_pool(process_num, initializer=None, initargs=None): if initializer is None: return Pool(process_num) elif initargs is None: return Pool(process_num, initializer) else: if not isinstance(initargs, tuple): raise TypeError('"initargs" must be a tuple') return Pool(process_num, initializer, initargs)
[docs]def track_parallel_progress(func, tasks, nproc, initializer=None, initargs=None, bar_width=50, chunksize=1, skip_first=False, keep_order=True, file=sys.stdout): """Track the progress of parallel task execution with a progress bar. The built-in :mod:`multiprocessing` module is used for process pools and tasks are done with :func:`Pool.map` or :func:`Pool.imap_unordered`. Args: func (callable): The function to be applied to each task. tasks (list or tuple[Iterable, int]): A list of tasks or (tasks, total num). nproc (int): Process (worker) number. initializer (None or callable): Refer to :class:`multiprocessing.Pool` for details. initargs (None or tuple): Refer to :class:`multiprocessing.Pool` for details. chunksize (int): Refer to :class:`multiprocessing.Pool` for details. bar_width (int): Width of progress bar. skip_first (bool): Whether to skip the first sample for each worker when estimating fps, since the initialization step may takes longer. keep_order (bool): If True, :func:`Pool.imap` is used, otherwise :func:`Pool.imap_unordered` is used. Returns: list: The task results. """ if isinstance(tasks, tuple): assert len(tasks) == 2 assert isinstance(tasks[0], Iterable) assert isinstance(tasks[1], int) task_num = tasks[1] tasks = tasks[0] elif isinstance(tasks, Iterable): task_num = len(tasks) else: raise TypeError( '"tasks" must be an iterable object or a (iterator, int) tuple') pool = init_pool(nproc, initializer, initargs) start = not skip_first task_num -= nproc * chunksize * int(skip_first) prog_bar = ProgressBar(task_num, bar_width, start, file=file) results = [] if keep_order: gen = pool.imap(func, tasks, chunksize) else: gen = pool.imap_unordered(func, tasks, chunksize) for result in gen: results.append(result) if skip_first: if len(results) < nproc * chunksize: continue elif len(results) == nproc * chunksize: prog_bar.start() continue prog_bar.update() prog_bar.file.write('\n') pool.close() pool.join() return results
[docs]def track_iter_progress(tasks, bar_width=50, file=sys.stdout): """Track the progress of tasks iteration or enumeration with a progress bar. Tasks are yielded with a simple for-loop. Args: tasks (list or tuple[Iterable, int]): A list of tasks or (tasks, total num). bar_width (int): Width of progress bar. Yields: list: The task results. """ if isinstance(tasks, tuple): assert len(tasks) == 2 assert isinstance(tasks[0], Iterable) assert isinstance(tasks[1], int) task_num = tasks[1] tasks = tasks[0] elif isinstance(tasks, Iterable): task_num = len(tasks) else: raise TypeError( '"tasks" must be an iterable object or a (iterator, int) tuple') prog_bar = ProgressBar(task_num, bar_width, file=file) for task in tasks: yield task prog_bar.update() prog_bar.file.write('\n')

© Copyright 2022, mmengine contributors. Revision 0549e1ce.

Built with Sphinx using a theme provided by Read the Docs.
Read the Docs v: v0.8.2
Versions
latest
stable
v0.8.2
v0.8.1
v0.8.0
v0.7.4
v0.7.3
v0.7.2
v0.7.1
v0.7.0
v0.6.0
v0.5.0
v0.4.0
v0.3.0
v0.2.0
Downloads
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.