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