lightning/pytorch_lightning/loggers/comet.py

252 lines
9.4 KiB
Python

"""
Comet
-----
"""
from argparse import Namespace
from typing import Optional, Dict, Union, Any
try:
from comet_ml import Experiment as CometExperiment
from comet_ml import ExistingExperiment as CometExistingExperiment
from comet_ml import OfflineExperiment as CometOfflineExperiment
from comet_ml import BaseExperiment as CometBaseExperiment
try:
from comet_ml.api import API
except ImportError: # pragma: no-cover
# For more information, see: https://www.comet.ml/docs/python-sdk/releases/#release-300
from comet_ml.papi import API # pragma: no-cover
from comet_ml.config import get_config, get_api_key
except ImportError: # pragma: no-cover
CometExperiment = None
CometExistingExperiment = None
CometOfflineExperiment = None
CometBaseExperiment = None
API = None
_COMET_AVAILABLE = False
else:
_COMET_AVAILABLE = True
import torch
from torch import is_tensor
from pytorch_lightning import _logger as log
from pytorch_lightning.loggers.base import LightningLoggerBase, rank_zero_experiment
from pytorch_lightning.utilities.exceptions import MisconfigurationException
from pytorch_lightning.utilities import rank_zero_only
class CometLogger(LightningLoggerBase):
r"""
Log using `Comet.ml <https://www.comet.ml>`_. Install it with pip:
.. code-block:: bash
pip install comet-ml
Comet requires either an API Key (online mode) or a local directory path (offline mode).
**ONLINE MODE**
Example:
>>> import os
>>> from pytorch_lightning import Trainer
>>> from pytorch_lightning.loggers import CometLogger
>>> # arguments made to CometLogger are passed on to the comet_ml.Experiment class
>>> comet_logger = CometLogger(
... api_key=os.environ.get('COMET_API_KEY'),
... workspace=os.environ.get('COMET_WORKSPACE'), # Optional
... save_dir='.', # Optional
... project_name='default_project', # Optional
... rest_api_key=os.environ.get('COMET_REST_API_KEY'), # Optional
... experiment_name='default' # Optional
... )
>>> trainer = Trainer(logger=comet_logger)
**OFFLINE MODE**
Example:
>>> from pytorch_lightning.loggers import CometLogger
>>> # arguments made to CometLogger are passed on to the comet_ml.Experiment class
>>> comet_logger = CometLogger(
... save_dir='.',
... workspace=os.environ.get('COMET_WORKSPACE'), # Optional
... project_name='default_project', # Optional
... rest_api_key=os.environ.get('COMET_REST_API_KEY'), # Optional
... experiment_name='default' # Optional
... )
>>> trainer = Trainer(logger=comet_logger)
Args:
api_key: Required in online mode. API key, found on Comet.ml. If not given, this
will be loaded from the environment variable COMET_API_KEY or ~/.comet.config
if either exists.
save_dir: Required in offline mode. The path for the directory to save local
comet logs. If given, this also sets the directory for saving checkpoints.
workspace: Optional. Name of workspace for this user
project_name: Optional. Send your experiment to a specific project.
Otherwise will be sent to Uncategorized Experiments.
If the project name does not already exist, Comet.ml will create a new project.
rest_api_key: Optional. Rest API key found in Comet.ml settings.
This is used to determine version number
experiment_name: Optional. String representing the name for this particular experiment on Comet.ml.
experiment_key: Optional. If set, restores from existing experiment.
offline: If api_key and save_dir are both given, this determines whether
the experiment will be in online or offline mode. This is useful if you use
save_dir to control the checkpoints directory and have a ~/.comet.config
file but still want to run offline experiments.
"""
def __init__(self,
api_key: Optional[str] = None,
save_dir: Optional[str] = None,
workspace: Optional[str] = None,
project_name: Optional[str] = None,
rest_api_key: Optional[str] = None,
experiment_name: Optional[str] = None,
experiment_key: Optional[str] = None,
offline: bool = False,
**kwargs):
if not _COMET_AVAILABLE:
raise ImportError('You want to use `comet_ml` logger which is not installed yet,'
' install it with `pip install comet-ml`.')
super().__init__()
self._experiment = None
# Determine online or offline mode based on which arguments were passed to CometLogger
api_key = api_key or get_api_key(None, get_config())
if api_key is not None and save_dir is not None:
self.mode = "offline" if offline else "online"
self.api_key = api_key
self._save_dir = save_dir
elif api_key is not None:
self.mode = "online"
self.api_key = api_key
elif save_dir is not None:
self.mode = "offline"
self._save_dir = save_dir
else:
# If neither api_key nor save_dir are passed as arguments, raise an exception
raise MisconfigurationException(
"CometLogger requires either api_key or save_dir during initialization."
)
log.info(f"CometLogger will be initialized in {self.mode} mode")
self.workspace = workspace
self.project_name = project_name
self.experiment_key = experiment_key
self._kwargs = kwargs
if rest_api_key is not None:
# Comet.ml rest API, used to determine version number
self.rest_api_key = rest_api_key
self.comet_api = API(self.rest_api_key)
else:
self.rest_api_key = None
self.comet_api = None
if experiment_name:
self.experiment.set_name(experiment_name)
self._kwargs = kwargs
@property
@rank_zero_experiment
def experiment(self) -> CometBaseExperiment:
r"""
Actual Comet object. To use Comet features in your
:class:`~pytorch_lightning.core.lightning.LightningModule` do the following.
Example::
self.logger.experiment.some_comet_function()
"""
if self._experiment is not None:
return self._experiment
if self.mode == "online":
if self.experiment_key is None:
self._experiment = CometExperiment(
api_key=self.api_key,
workspace=self.workspace,
project_name=self.project_name,
**self._kwargs
)
self.experiment_key = self._experiment.get_key()
else:
self._experiment = CometExistingExperiment(
api_key=self.api_key,
workspace=self.workspace,
project_name=self.project_name,
previous_experiment=self.experiment_key,
**self._kwargs
)
else:
self._experiment = CometOfflineExperiment(
offline_directory=self.save_dir,
workspace=self.workspace,
project_name=self.project_name,
**self._kwargs
)
return self._experiment
@rank_zero_only
def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
params = self._convert_params(params)
params = self._flatten_dict(params)
self.experiment.log_parameters(params)
@rank_zero_only
def log_metrics(
self,
metrics: Dict[str, Union[torch.Tensor, float]],
step: Optional[int] = None
) -> None:
assert rank_zero_only.rank == 0, 'experiment tried to log from global_rank != 0'
# Comet.ml expects metrics to be a dictionary of detached tensors on CPU
for key, val in metrics.items():
if is_tensor(val):
metrics[key] = val.cpu().detach()
self.experiment.log_metrics(metrics, step=step)
def reset_experiment(self):
self._experiment = None
@rank_zero_only
def finalize(self, status: str) -> None:
r"""
When calling ``self.experiment.end()``, that experiment won't log any more data to Comet.
That's why, if you need to log any more data, you need to create an ExistingCometExperiment.
For example, to log data when testing your model after training, because when training is
finalized :meth:`CometLogger.finalize` is called.
This happens automatically in the :meth:`~CometLogger.experiment` property, when
``self._experiment`` is set to ``None``, i.e. ``self.reset_experiment()``.
"""
self.experiment.end()
self.reset_experiment()
@property
def save_dir(self) -> Optional[str]:
return self._save_dir
@property
def name(self) -> str:
return str(self.experiment.project_name)
@property
def version(self) -> str:
return self.experiment.id
def __getstate__(self):
state = self.__dict__.copy()
state["_experiment"] = None
return state