lightning/pytorch_lightning/loggers/comet.py

230 lines
8.3 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
_COMET_AVAILABLE = True
except ImportError: # pragma: no-cover
CometExperiment = None
CometExistingExperiment = None
CometOfflineExperiment = None
CometBaseExperiment = None
API = None
_COMET_AVAILABLE = False
import torch
from torch import is_tensor
from pytorch_lightning import _logger as log
from pytorch_lightning.loggers.base import LightningLoggerBase
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
save_dir: Required in offline mode. The path for the directory to save local comet logs
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.
"""
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,
**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
if 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:
try:
self.name = experiment_name
except TypeError:
log.exception("Failed to set experiment name for comet.ml logger")
self._kwargs = kwargs
@property
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:
# 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 name(self) -> str:
return str(self.experiment.project_name)
@name.setter
def name(self, value: str) -> None:
self.experiment.set_name(value)
@property
def version(self) -> str:
return self.experiment.id