class CometMLMonitor(MonitorBase):
"""
Send data to https://www.comet.ml.
Note:
1. comet_ml requires you to `import comet_ml` before importing tensorflow or tensorpack.
2. The "automatic output logging" feature of comet_ml will make the training progress bar appear to freeze.
Therefore the feature is disabled by default.
"""
def __init__(self, experiment=None, api_key=None, tags=None, **kwargs):
"""
Args:
experiment (comet_ml.Experiment): if provided, invalidate all other arguments
api_key (str): your comet.ml API key
tags (list[str]): experiment tags
kwargs: other arguments passed to :class:`comet_ml.Experiment`.
"""
if experiment is not None:
self._exp = experiment
assert api_key is None and tags is None and len(kwargs) == 0
else:
from comet_ml import Experiment
kwargs.setdefault(
'log_code', True
) # though it's not functioning, git patch logging requires it
kwargs.setdefault('auto_output_logging', None)
self._exp = Experiment(api_key=api_key, **kwargs)
if tags is not None:
self._exp.add_tags(tags)
self._exp.set_code(
"Code logging is impossible because there are too many files ...")
self._exp.log_dependency('tensorpack', __git_version__)
@property
def experiment(self):
"""
The :class:`comet_ml.Experiment` instance.
"""
return self._exp
def _before_train(self):
self._exp.set_model_graph(tf.get_default_graph())
@HIDE_DOC
def process_scalar(self, name, val):
self._exp.log_metric(name, val, step=self.global_step)
def _after_train(self):
self._exp.end()
def _after_epoch(self):
self._exp.log_epoch_end(self.epoch_num)
class CometMLMonitor(MonitorBase):
"""
Send scalar data and the graph to https://www.comet.ml.
Note:
1. comet_ml requires you to `import comet_ml` before importing tensorflow or tensorpack.
2. The "automatic output logging" feature of comet_ml will make the training progress bar appear to freeze.
Therefore the feature is disabled by default.
"""
def __init__(self, experiment=None, tags=None, **kwargs):
"""
Args:
experiment (comet_ml.Experiment): if provided, invalidate all other arguments
tags (list[str]): experiment tags
kwargs: arguments used to initialize :class:`comet_ml.Experiment`,
such as project name, API key, etc.
Refer to its documentation for details.
"""
if experiment is not None:
self._exp = experiment
assert tags is None and len(kwargs) == 0
else:
from comet_ml import Experiment
kwargs.setdefault(
'log_code', True
) # though it's not functioning, git patch logging requires it
kwargs.setdefault('auto_output_logging', None)
self._exp = Experiment(**kwargs)
if tags is not None:
self._exp.add_tags(tags)
self._exp.set_code("Code logging is impossible ...")
self._exp.log_dependency('tensorpack', __git_version__)
@property
def experiment(self):
"""
The :class:`comet_ml.Experiment` instance.
"""
return self._exp
def _before_train(self):
self._exp.set_model_graph(tf.get_default_graph())
@HIDE_DOC
def process_scalar(self, name, val):
self._exp.log_metric(name, val, step=self.global_step)
@HIDE_DOC
def process_image(self, name, val):
self._exp.set_step(self.global_step)
for idx, v in enumerate(val):
log_name = "{}_step{}{}".format(
name, self.global_step, "_" + str(idx) if len(val) > 1 else "")
self._exp.log_image(v,
image_format="jpeg",
name=log_name,
image_minmax=(0, 255))
def _after_train(self):
self._exp.end()
def _after_epoch(self):
self._exp.log_epoch_end(self.epoch_num)
