import logging
from delira.utils.decorators import make_deprecated
from ..multistream_handler import MultiStreamHandler
from .visdom_imgsave_handler import VisdomImageSaveHandler
from ..trixi_handler import TrixiHandler
[docs]@make_deprecated(TrixiHandler)
class VisdomImageSaveStreamHandler(logging.Handler):
"""
Logs metrics to streams, metric plots and images to visdom
.. deprecated:: 0.1
:class:`VisdomImageSaveStreamHandler` will be removed in next release
and is
deprecated in favor of ``trixi.logging`` Modules
.. warning::
:class:`VisdomImageSaveStreamHandler` will be removed in next release
See Also
--------
`Visdom`
:class:`VisdomImageHandler`
:class:`MultiStreamHandler`
:class:`TrixiHandler`
"""
def __init__(self, port, prefix, log_freq_train, log_freq_val=1e10,
save_dir_train="./images_train", save_dir_val="./images_val",
save_freq_train=1, save_freq_val=1, log_freq_img=1,
streams=[], level=logging.NOTSET, **kwargs):
"""
Parameters
----------
port : int
port of visdom-server
prefix : str
prefix of environment names
log_freq_train : int
Defines logging frequency for scores in train mode
log_freq_val : int
Defines logging frequency for scores in validation mode
save_dir_train : str
path to which the training images should be saved (must not yet be
existent)
save_dir_val : string (default:None)
path to which the training images should be saved (must not yet be
existent)
save_freq_train : int (default: 1)
frequency with which images are saved during training
save_freq_val : int (default: 1)
frequency with which images are saved during validation
streams : list of streams with write()-attribute
streams which are passed to StreamHandlers
level : int (default: logging.NOTSET)
logging level
**kwargs :
additional keyword arguments which are directly passed to visdom
"""
super().__init__(level)
self._visdom_image_handler = VisdomImageSaveHandler(
port, prefix, log_freq_train, log_freq_val=log_freq_val,
save_freq_train=save_freq_train, save_freq_val=save_freq_val,
save_dir_train=save_dir_train, save_dir_val=save_dir_val,
log_freq_img=log_freq_img, level=level, **kwargs)
self._stream_handler = MultiStreamHandler(*streams, level=level)
[docs] def emit(self, record: dict):
"""
Logs metrics to streams, metric plots and images to visdom
Parameters
----------
record: dict
entities to log
"""
if isinstance(record.msg, dict):
self._visdom_image_handler.emit(record)
_, _ = record.msg.pop("scalars", {}), record.msg.pop("images", {})
if record.msg:
self._stream_handler.emit(record)