mmcv.runner.hooks.logger.neptune 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook

[文档]@HOOKS.register_module() class NeptuneLoggerHook(LoggerHook): """Class to log metrics to NeptuneAI. It requires `neptune-client` to be installed. Args: init_kwargs (dict): a dict contains the initialization keys as below: - project (str): Name of a project in a form of namespace/project_name. If None, the value of NEPTUNE_PROJECT environment variable will be taken. - api_token (str): User’s API token. If None, the value of NEPTUNE_API_TOKEN environment variable will be taken. Note: It is strongly recommended to use NEPTUNE_API_TOKEN environment variable rather than placing your API token in plain text in your source code. - name (str, optional, default is 'Untitled'): Editable name of the run. Name is displayed in the run's Details and in Runs table as a column. Check for more init arguments. interval (int): Logging interval (every k iterations). ignore_last (bool): Ignore the log of last iterations in each epoch if less than `interval`. reset_flag (bool): Whether to clear the output buffer after logging by_epoch (bool): Whether EpochBasedRunner is used. .. _NeptuneAI: """ def __init__(self, init_kwargs=None, interval=10, ignore_last=True, reset_flag=True, with_step=True, by_epoch=True): super(NeptuneLoggerHook, self).__init__(interval, ignore_last, reset_flag, by_epoch) self.import_neptune() self.init_kwargs = init_kwargs self.with_step = with_step def import_neptune(self): try: import as neptune except ImportError: raise ImportError( 'Please run "pip install neptune-client" to install neptune') self.neptune = neptune = None @master_only def before_run(self, runner): if self.init_kwargs: = self.neptune.init(**self.init_kwargs) else: = self.neptune.init() @master_only def log(self, runner): tags = self.get_loggable_tags(runner) if tags: for tag_name, tag_value in tags.items(): if self.with_step:[tag_name].log( tag_value, step=self.get_iter(runner)) else: tags['global_step'] = self.get_iter(runner)[tag_name].log(tags) @master_only def after_run(self, runner):