mmcv.runner.hooks.logger.tensorboard 源代码

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp

from mmcv.utils import TORCH_VERSION, digit_version
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook

[文档]@HOOKS.register_module() class TensorboardLoggerHook(LoggerHook): def __init__(self, log_dir=None, interval=10, ignore_last=True, reset_flag=False, by_epoch=True): super(TensorboardLoggerHook, self).__init__(interval, ignore_last, reset_flag, by_epoch) self.log_dir = log_dir @master_only def before_run(self, runner): super(TensorboardLoggerHook, self).before_run(runner) if (TORCH_VERSION == 'parrots' or digit_version(TORCH_VERSION) < digit_version('1.1')): try: from tensorboardX import SummaryWriter except ImportError: raise ImportError('Please install tensorboardX to use ' 'TensorboardLoggerHook.') else: try: from torch.utils.tensorboard import SummaryWriter except ImportError: raise ImportError( 'Please run "pip install future tensorboard" to install ' 'the dependencies to use torch.utils.tensorboard ' '(applicable to PyTorch 1.1 or higher)') if self.log_dir is None: self.log_dir = osp.join(runner.work_dir, 'tf_logs') self.writer = SummaryWriter(self.log_dir) @master_only def log(self, runner): tags = self.get_loggable_tags(runner, allow_text=True) for tag, val in tags.items(): if isinstance(val, str): self.writer.add_text(tag, val, self.get_iter(runner)) else: self.writer.add_scalar(tag, val, self.get_iter(runner)) @master_only def after_run(self, runner): self.writer.close()