""" 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 `_. 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