mirror of https://github.com/open-mmlab/mmcv.git
[Enhancement] Improve the docstring of PaviLoggerHook (#2060)
* Add parameter configuration description of summarywriter to MMCV PAVI hook. * Typo repaired * fix typo with suggested change * self.init_kwargs lines modified.pull/2084/head
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@ -19,7 +19,22 @@ class PaviLoggerHook(LoggerHook):
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"""Class to visual model, log metrics (for internal use).
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Args:
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init_kwargs (dict): A dict contains the initialization keys.
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init_kwargs (dict): A dict contains the initialization keys as below:
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- name (str, optional): Custom training name. Defaults to None,
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which means current work_dir.
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- project (str, optional): Project name. Defaults to "default".
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- model (str, optional): Training model name. Defaults to current
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model.
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- session_text (str, optional): Session string in YAML format.
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Defaults to current config.
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- training_id (int, optional): Training ID in PAVI, if you want to
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use an existing training. Defaults to None.
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- compare_id (int, optional): Compare ID in PAVI, if you want to
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add the task to an existing compare. Defaults to None.
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- overwrite_last_training (bool, optional): Whether to upload data
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to the training with the same name in the same project, rather
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than creating a new one. Defaults to False.
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add_graph (bool): Whether to visual model. Default: False.
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add_last_ckpt (bool): Whether to save checkpoint after run.
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Default: False.
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@ -59,8 +74,8 @@ class PaviLoggerHook(LoggerHook):
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if not self.init_kwargs:
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self.init_kwargs = dict()
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self.init_kwargs['name'] = self.run_name
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self.init_kwargs['model'] = runner._model_name
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self.init_kwargs.setdefault('name', self.run_name)
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self.init_kwargs.setdefault('model', runner._model_name)
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if runner.meta is not None:
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if 'config_dict' in runner.meta:
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config_dict = runner.meta['config_dict']
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@ -83,7 +98,7 @@ class PaviLoggerHook(LoggerHook):
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config_dict = json.loads(
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mmcv.dump(config_dict, file_format='json'))
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session_text = yaml.dump(config_dict)
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self.init_kwargs['session_text'] = session_text
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self.init_kwargs.setdefault('session_text', session_text)
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self.writer = SummaryWriter(**self.init_kwargs)
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def get_step(self, runner) -> int:
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