Comet Python SDK releases¶
The following is a history of released comet_ml
versions. It does not list everything that was changed in a release, but does mention the highlights and all public-facing additions, changes, and deprecations.
You can install any one of the following released version numbers. The full list of releases is at Python Package Index.
For installation of the Comet Python SDK on air-gapped computers, see Offline Installation.
Note that items that refer to Experiment also apply to ExistingExperiment, OfflineExperiment, and ExistingOfflineExperiment.
Release 3.47.0¶
Release date: Sep 26, 2024
- Added module level
flush
andend
functions for the currently running experiment. - Update the functions
comet_ml.integrations.sklearn.load_model
andcomet_ml.integrations.pytorch.load_model
. Now they no longer show warnings when the model is downloaded from model registry.
Release 3.46.0¶
Release date: Sep 19, 2024
- Added
APIExperiment.get_artifact_lineage
method. - Fixed bug when
register_model
operations were ignored when uploading an offline experiment.
Release 3.45.1¶
Release date: Sep 13, 2024
- Fixed bug when experiments in colab didn't log parameters if
exp.end()
is not called.
Release 3.45.0¶
Release date: Aug 28, 2024
- Added flag to disable normalization in
Experiment.log_audio
- Added comet_ml.error_mode()
- Added serialization support for numpy arrays and torch tensors inside JSON assets to log
- Fixed bug when annotations are logged for images, that didn't have annotations in log_image method
- DEBUG mode for console logging is now forbidden
Release 3.44.4¶
Release date: Aug 7, 2024
- Align Name size limits across Comet product, those limits are now higher.
- Improved error message when image conversion failed by pillow library when logging images with
Experiment.log_image
. - Keras integration updated to support tensorflow 2.16+.
- Fixed bug when Ray integration could not finish work correctly if OfflineExperiment was used.
Release 3.44.3¶
Release date: Jul 24, 2024
- Ray integration updated to support automatic failure retrying.
- Fixed bug when SDK did not prevent new images from being uploaded after hard limit was reached for the experiment.
Release 3.44.2¶
Release date: Jul 23, 2024
- Fixed XGBoost v2 integration
- Fixed bug when in some circumstances Comet printed unwanted errors about GPU logging
- Added API objects for building image annotations
- Storage usage optimizations
- Comet now suggests correct config names if it detects incomplete ones provided by user
- Fixed TensorboardX integration
- Major docstrings update
Release 3.44.1¶
Release date: Jul 9, 2024
- Fix a potential crash in
comet check
- Improve message when trying to write config to an existing file without the force flag
- Fix XGBoost integration in case of failure to retrieve parameters
Release 3.44.0¶
Release date: Jul 8, 2024
- Added
comet_ml.login()
as newer alternative tocomet_ml.init()
(init()
is deprecated now). CLI tool was updated accordingly. - Various improvements in error processing and some user-facing error messages
Release 3.43.2¶
Release date: Jun 21, 2024
- Error and warning messages:
- added more error rate filtering
- reworked misleading messages to make them clearer.
- Added dictionary flattening logic to
Experiment.log_metrics
- Fixed the bug in CLI tool when sometimes arguments failed to be parsed because of IndexError
- Added possibility to set experiment name and tags in ExperimentConfig for comet_ml.start
Release 3.43.1¶
Release date: Jun 13, 2024
- Improvements in file uploads resiliency
- Fixed the pytorch auto-logger bug when loss wasn't logged if training
loss.backward
wasn't called not in the same thread where experiment was created. API.get_metrics_df()
major logic update- Improvements in error processing and user-facing error messages
Release 3.43.0¶
Release date: May 29, 2024
- Added
delete_parameter
anddelete_parameters
methods toAPIExperiment
- Updated ray integration to support usage of already running experiments and offline experiments.
Release 3.42.1¶
Release date: May 22, 2024
- WebSockets excluded from requirements
- API.download_experiment_asset speedup
- Added inputs validation for
Experiment.log_curve
- Added inputs validation for
Experiment.add_tag
andExperiment.add_tags
- Added new error message if experiment is tried to be logged in LLM project
- Added package to conda for python 3.12
Release 3.42.0¶
Release date: May 10, 2024
- Introduced new method -
API.get_metrics_df
- Major Experiment docstrings update
- Allowed customization of the experiment name in Ray integration
comet_ml.integration.pytorch.watch
no longer fails when tracking non-trainable layersTestExperiment
now raises an exception only if comet error message was logged- Added annotation validation to
Experiment.log_image
Release 3.41.0¶
Release date: Apr 24, 2024
- New behavior for get_metric, get_other, get_parameter, get_tags methods in ExistingExperiment. Now returned values are synced with the backend. It's possible to get latest values logged in previous Experiment run or values from another ExistingExperiment instance running in parallel.
- Fix bug when pytorch model definition wasn't logged if watch function is used
- APIExperiment.get_metrics speedup
- Fixed bug when failed to upload images with dots in the name
- Experiment.flush() now properly returns bool value
- Added log_video method to APIExperiment
Release 3.40.0¶
Release date: Apr 11, 2024
- The experiment name will now be displayed in the experiment summary
- Fixed bug with CUDA_VISIBLE_DEVICES=-1 that lead to user facing error messages
- Introduced new method called
comet_ml.get_running_experiment()
that returns the running experiment if one exists - Introduced functionality in the SDK to determine the Comet URL to log data to based on the API key used. This means that you won't need to specify the
COMET_URL_OVERRIDE
environment variable for on-premise deployments. Note: for this functionality to be enabled on your on-premise deployment please contact our deployment team.
Release 3.39.2¶
Release date: Mar 26, 2024
- Introduced
TestExperiment
(alpha version) - Not synced remote assets on model download are now skipped
- Introduced new SDK method for API experiment:
APIExperiment.delete_tags(tags)
Release 3.39.1¶
Release date: Mar 18, 2024
- Improved CPU system metrics logging, fixed some cases when it could stop working at all
- Fixed bug when model file created by pytorch.log_model had incorrect name with
OfflineExperiment
Release 3.39.0¶
Release date: Mar 8, 2024
- System metrics interval decreased from 60 to 30 seconds
- bugfix:
API.get_archived_experiments
returns what it should return now - Code name can now be overwritten in
experiment.log_code
- Artifact will now raise an exception on creation if its name exceeds 100 characters
- Major multiprocessing compatibility improvements (fixed hangings on upload at the end of worker process).
Release 3.38.1¶
Release date: Feb 23, 2024
- Improved SDK error message when trying to log an artifact for a version that has been deleted
- Added support for seaborn plots (
matplotlib.axes.Axes
objects) in log_figure
Release 3.38.0¶
Release date: Feb 16, 2024
- Added support for Pytorch Histogram Logging
Release 3.37.2¶
Release date: Feb 13, 2024
- Disabled mode no longer requires API key
- Internal improvements and optimizations
Release 3.37.1¶
Release date: Feb 2, 2024
- Internal improvements and optimizations
Release 3.37.0¶
Release date: Jan 23, 2024
- Introduced new
Experiment.log_points_3d
method - bugfix: fastai autologger no longer ignores
auto_metric_logging
andauto_param_logging
.
Release 3.36.1¶
Release date: Jan 18, 2024
- bugfix: now GPU logging no longer stops if some device metric is not available, the rest of them are still logged
Release 3.36.0¶
Release date: Jan 12, 2024
comet_ml.init()
now supports anonymous mode
Release 3.35.6¶
Release date: Jan 11, 2024
- FastAI integration was updated to support version 2
- Introduced APIExperiment.set_state method (possible states: running, crashed, finished)
Release 3.35.5¶
Release date: Dec 14, 2023
- Made artifact_type optional in
Artifact.__init__
- It's possible now to specify the name of the asset in
APIExperiment.log_asset
(before it was always a full file name)
Release 3.35.4¶
Release date: Dec 7, 2023
- Added ability to get python panel experiments
- UX improvements to running Experiment from AWS Lambda function
- Added new validation to inputs for register_model
Release 3.35.3¶
Release date: Nov 10, 2023
- Fixed bug when None values were incorrectly shown in summary
- Added support for ydata-profiling
- Added new automatic naming scheme for models in MLFlow integration
Release 3.35.2¶
Release date: Nov 3, 2023
- Introduced callback for uploading experiment ZIP to S3 bucket if experiment is in offline mode in the end.
- Major logging optimization
Release 3.35.1¶
Release date: Oct 26, 2023
- Introduced new GPU and disk usage system metrics
Release 3.35.0¶
Release date: Oct 23, 2023
- Major improvement: experiment now tries to reconnect after connection was lost. All pending data logged during offline period will be uploaded to Comet.
- Pytorch autologger is now compatible with accelerate library.
Release 3.34.0¶
Release date: Oct 17, 2023
- Introduced
Experiment.log_video
method - Introduced
Model.get_version_history
method
Release 3.33.12¶
Release date: Oct 16, 2023
- It is now possible to set a callback to process an experiment zip file at the end of experiment if the connection is lost.
- Added support for nested params to
APIExperiment.log_parameters
. - Bug fix:
APIExperiment.log_metric
no longer sends a timestamp instead of an epoch.
Release 3.33.11¶
Release date: Sep 28, 2023
- Added new
APIExperiment.get_state
method to return the state of an experiment (running, finished, crashed) - Fixed issue when Comet was running within AWS Lambda functions
Release 3.33.10¶
Release date: Sep 6, 2023
- Added new
Experiment.log_optimization
method - Fixed string metric logging issue on experiment start
- Fix vertex integration crashing
Experiment.register_model
now has option to be run synchronously- deprecated copy_to_tmp in various
Experiment.log_*
methods
Release 3.33.9¶
Release date: Aug 22, 2023
- Updated Vertex integration
- Users can configure retry policy when connectivity to the Comet server is lost
- Comet Keras callback now allows to set the initial validation step for resume training workflows
- Network metrics in ExistingExperiment are disabled by default now
Release 3.33.8¶
Release date: Aug 4, 2023
- Comet no longer uploads images if the limit is exceeded
- Deprecated
copy_to_tmp
argument inExperiment.log_asset
- Added conda build for python 3.11
Release 3.33.7¶
- Improved exceptions handling in sagemaker integration
- Now experiment API object can be passed to sagemaker integration functions
- Introduced
CometVertexPipelineLogger
with the support of safe API key sharing - Experiments don't hang as running in UI after fallback to offline mode
Release 3.33.6¶
Release date: July 12, 2023
- Keras callback now uses separate step for validation batches
- CPU, GPU, Network metrics log interval is now configurable
- bugfix: Fixed logging more than 10 nested params issue (using dictionaries)
Release 3.33.5¶
Release date: June 22, 2023
- Introduced remote models logging and loading support
- Experiment now logs network system metrics
Experiment.log_parameters
now supports nested dictionaries that have a new view in UIExperiment.log_image
now has metadata argument- bugfix: comet keras callback now takes initial step from the experiment and epoch from keras
- bugfix:
urllib3
required version softened. Previous version could lead to installation problems.
Release 3.33.4¶
Release date: June 7, 2023
- Update
urllib3
Python dependency to version 2.0 - Added support for CSV format with espace character in
Experiment.log_table()
- Bugfix: git metadata and git-patch sections were sometimes missing from the experiment summary
Release 3.33.3¶
Release date: May 16, 2023
- File assets and artifacts are uploaded to S3 directly leading to improved upload speeds
- Update log message copy when optimizer timesout
Release 3.33.2¶
Release date: May 12, 2023
- Support for storing and retrieving a Comet API key using AWS Secret Manager
Release 3.33.1¶
Release date: May 8, 2023
- Various SDK improvements
Release 3.33.0¶
Release date: May 1, 2023
- Novel Model Approval Process API supporting new tags and status fields
Release 3.32.9¶
Release date: Apr 26, 2023
- Updated the OpenAI integration to support Chat Completions
- Release new SDK methods for saving and loading Scikit Learn methods - Read the docs here
Release 3.32.8¶
Release date: Apr 17, 2023
- New Integration with OpenAI SDK - Read the docs here
- Update to the memory metric reported by the SDK
- Per-core CPU system metric no longer sent by default
- Optimizer
get_id()
method returns only id value without theCOMET_OPTIMIZER_ID
prefix
Release 3.32.7¶
Release date: Apr 09, 2023
- SDK logs now appear in color on your terminal
- Bugfix: metaflow integration logged some hyper parameters even when
auto_param_logging=False
Release 3.32.6¶
Release date: Mar 30, 2023
- Updated logging of some BI events so they are not triggered as often
Release 3.32.5¶
Release date: Mar 24, 2023
- Add upper bound for everett version for python>=3.6 to properly select default logging infastructure
- Fixed experiment summary to properly display HTML assets logged section
- Git metadata logging can now be disabled separately from source code logging
Release 3.32.4¶
Release date: Mar 10, 2023
- Support for storing and retrieving a Comet API key using GCP Secret Manager
- Support in
Experiment.log_code
for an extended set of source code file extensions:.py
,.text
,.yaml
,.ipynb
, and.sh
Release 3.32.3¶
Release date: Mar 01, 2023
- Bug fix: Fix issue registering models with multiple files (a folder)
- Bug fix: Metaflow integration could crash on methods not decorated with @step
- Introduced support for logging values specified via environment variables with the
COMET_LOG_OTHER_
prefix - Introduced new Experiment.flush() method that is blocking until all pending data is logged to Comet. Works like
.end()
but does not end the experiment
Release 3.32.2¶
Release date: Feb 16, 2023
- Highlight the new Pytorch model saving and loading functions in console output logs
- Support for
overwrite
parameter inExperiment.log_code
Release 3.32.1¶
Release date: Feb 10, 2023
- Fixed the Metaflow decorator for latest version of Metaflow
- Fixed issue with experiments not reporting their status during long training run
- Fixed issue with Artifact download when absolute paths where used instead of relative paths
Release 3.32.0¶
Release date: Jan 26, 2023
- Integration with AWS SageMaker
- Support for distributed training with Ray
Release 3.31.22¶
Release date: Jan 10, 2023
- Logging metaflow
origin_run_id
, enabling easier searches for original experiment in case of resuming a failed flow run - SDK to sends
has_crashed
flag to Comet backend to signify unhandled exceptions that cause user's script to crash - The
Experiment.log_image
now allows anannotations
parameter, which will be used in the future for bounding boxes and segmentation
Release 3.31.21¶
Release date: December 23, 2022
- Release new Gymnasium integration
- Improvement to CPU usage reports - Now only the CPU usage for the Python process tree is reported to Comet
- Remove some INFO-level log messages related to GPU metrics logging
Release 3.31.20¶
Release date: December 11, 2022
- GPU detection based on
CUDA_VISIBLE_DEVICES
environment variable, as a result GPU metrics will be displayed only for the GPUs used by the training run - Improve error message when using Experiment with an already existing experiment key
- Bugfix: Log validation batch metrics under a proper namespace in Keras
- Bugfix: Throttling message was not shows under certain circumstances
- Bugfix: Properly handle AttributeError in RandomForestClassifier when using Comet's Scikit-Learn integration
Release 3.31.19¶
Release date: November 16, 2022
- Bugfix: add missing registration of the
comet_ml.spacy.logger.v1
Python entry point required for integration with spaCy logging
Release 3.31.18¶
Release date: November 14, 2022
- Streamlined Model Registration by adding the method Experiment.register_model(...)
- FallbackToOffline: if network connection is lost, an offline archive will be made available for later upload
Release 3.31.17¶
Release date: November 08, 2022
- Fix traceback emitted by logging system in some edge cases
Release 3.31.16¶
Release date: October 30, 2022
- Fix faulty retry mechanism related to image upload.
- Fix metaflow logging system tags.
- Fix bug in api experiment symlink creation.
- Metaflow: Integration with project decorator.
- Add hparams support for tensorboard logger (tensorflow).
Release 3.31.15¶
Release date: October 3, 2022
- Logs include timestamps when in DEBUG mode.
- No longer log CLI flags when Metaflow integration is used
- Pytorch integration improvements: Methods to save and load Pytorch models
- Support for Pytorch Tensorboard
- Bugfix: restore summary in output capture
Release 3.31.14¶
Release date: September 16, 2022
- Fix broken Metaflow support.
Release 3.31.13¶
Release date: September 14, 2022
- Fix data loss issue introduced by new Thread Pool from 3.31.10
- Fix SDK crash induced by parameters with numpy array values in some circumstances.
- Metaflow integration: introduce a
comet_skip
decorator to prevent creating a live experiment for steps where it is unwanted - Python SDK now uses comet.com as its default backend domain
- Metaflow integration: integrate with Metaflow cards
Release 3.31.12¶
Release date: August 26, 2022
- Pin version for
websocket-client
as>=0.55.0,<1.4.0
so as to avoid recently released broken version.
Release 3.31.11¶
Release date: August 22, 2022
- Drop support for Python 2.
Release 3.31.10¶
Release date: August 21, 2022
- Bugfix: fix crash on AWS Lambda with Python>3.6
Release 3.31.9¶
Release date: August 19, 2022
- Removed dependency on
nvidia_ml_py3
. The functionality is replaced by including the code fromnvidia-ml-py
as part of the Comet Python SDK code. Note thatnvidia-ml-py
package is not a dependency of the Comet Python SDK. - Bugfix: remote synced asset may now be logged without specifying
logical_path
. - When an experiment is throttled, a more meaningful message is now logged to the user.
- Introduce sanitation of Metaflow environment.
- Extend error reporting to comet backend for various error conditions.
Release 3.31.8¶
Release date: August 15, 2022
- Fix broken
import comet_ml
statement when used with Hugging Facedatasets
library on Google Colab.
Release 3.31.7¶
Release date: July 26, 2022
- Sanitize environment information from Vertex pipeline JSON.
- Sanitize environment information from Kubeflow pipeline JSON.
- Invalid API Key error message now includes the hostname for the backend server.
- Stop logging source code from within the Metaflow library.
- Add error reporting for various conditions.
Release 3.31.6¶
Release date: July 13, 2022
- Rename Metaflow integration attribute
pipeline_comet_experiment_key
torun_comet_experiment_key
. - Remove warning when running a Metaflow flow that does not define parameters.
- Filter out environment variable when logging the conda environment information.
- Improve parsing of command line arguments.
Release 3.31.5¶
Release date: June 25, 2022
- Change Experiment notification title to include user and Experiment name.
- Fix
Histogram.add()
with counts. - Update Metaflow integration to allow to access the Comet Experiment id for the current Metaflow run through the
self.pipeline_comet_experiment_key
attribute.
Release 3.31.3¶
Release date: June 2, 2022
- Add automatic logging of the environment creating the Vertex Pipeline. See the Vertex Integration documentation for more information.
Release 3.31.2¶
Release date: May 31, 2022
- Fixed linting problem caused by wrong type-hint comments.
- Renamed potentially conflicting callback functions - reduce chances of name conflicts with users.
- Add support for scikit-learn 1.1.0.
Release 3.31.1¶
Release date: May 12, 2022
- Preliminary work to improve reliability and speed of Metric logging.
Release 3.31.0¶
Release date: May 05, 2022
Temporarily disable logging of Conda environments. Starting from Release 3.27.0, we logged the Conda environment details. That information included any environment variable set in the Conda environment.
New artifact methods to update artifact tags
LoggedArtifact.update_artifact_tags
, version tagsLoggedArtifact.update_version_tags
and version aliasesupdate_aliases
.We are planning to drop support for Python 2.7. Version 3.30.0 was the last version supporting Python 2.7 as a Conda package.
Release 3.30.0¶
Release date: April 27, 2022
- When calling
Artifact.add_remote
with a remote URI that starts withgs://
, the Python SDK try to list objects matching the Google Storage link and log individual objects as synced remote artifact, including their version if object versioning is enabled on the GS bucket. This behavior can be turned off withsync_mode=False
- When downloading an Artifact Version assets with
Artifact.download
, if the Artifact Version contains synced remote assets, the Python SDK will try to download the objects from Google Storage to the target directory. This behavior can be turned off withsync_mode=False
. - Improve error message when the project name is too long.
- Improve Vertex and Kubeflow integrations by logging individual task names.
- Use the same default offline directory for the MLflow integration and for Offline Experiments.
Release 3.29.0¶
Release date: April 21, 2022
- Add official Conda package for Python 3.10.
- When calling
Artifact.add_remote
with a remote URI that starts withs3://
, the Python SDK try to list objects matching the S3 link and log individual blobs as synced remote artifact, including their version if object versioning is enabled on the S3 bucket. This behavior can be turned off withsync_mode=False
- When downloading an Artifact Version assets with
Artifact.download
, if the Artifact Version contains synced remote assets, the Python SDK will try to download the objects from S3 to the target directory. This behavior can be turned off withsync_mode=False
. - Parameter
asset_type
of theArtifact.add_remote
is now deprecated, it was not used so far. - The Predictor is now fully removed, it was previously deprecated.
Release 3.28.3¶
Release date: April 11, 2022
- Improve reliability of large file uploads with some L4 load-balancers.
Release 3.28.2¶
Release date: March 16, 2022
- Fixed APIExperiment.get_asset(..., stream=True) to correctly return a streamed response and updated its docstring to include how to use it.
- When a metric value cannot be converted to a native Python number, the Python SDK now displays a warning as the result might be invalid.
- Fixed support of
COMET_OPTIMIZER_URL
configuration environment variable without an ending slash.
Release 3.28.1¶
Release date: March 14, 2022
- Switch some common Conda-related error logs from WARNING to DEBUG.
Release 3.28.0¶
Release date: March 03, 2022
- Optimizer URL is now automatically computed based on
COMET_URL_OVERRIDE
for on-premise installation. COMET_WS_URL_OVERRIDE
can now includes a trailing slash.- When running inside a Container using CGroups V2, the CPU limits are now taken into account to limits the number of parallel file upload and file download.
- (We now uses class based XGBoost callbacks).
Release 3.27.0¶
Release date: February 24, 2022
- When running inside a Conda environment, Conda package, channels and configuration are now logged as Experiment assets.
- Add Kubeflow and Vertex integration.
Release 3.26.1¶
Release date: February 17, 2022
- Improve compatibility of the console logger in some Notebook environments.
Release 3.26.0¶
Release date: February 11, 2022
- When running inside a Pydev Console, the Experiment object might not have enough time to send everything. In that case, you will need to explicitly call Experiment.end. The Python SDK will show you a warning to remember to add it. This can happen in various situation like with Pycharm run action when the
Run with Python console
option is activated. - Added APIExperiment.add_tag(tag) for adding an single tag to an APIExperiment.
Release 3.25.0¶
Release date: January 28, 2022
- When running the Comet Optimizer, the optimizer name is now logged. The name is set in the optimizer specification, or given a default generated ID if unset.
- Importing the Python Comet SDK is now allowed after importing other machine-learning libraries. Previously, this raised an exception and stopped the script. Now, the script will continue to run. However, this will result in the lack of many important auto-logged items.
- You can now finely tune the number of threads used for file upload and downloads by setting the
comet.internal.worker_count
config key (COMET_INTERNAL_WORKER_COUNT
environment variable). The value set should be a number.
Release 3.24.2¶
Release date: January 20, 2022
- When using the Optimizer with the Optimizer.get_parameters() method, the hyper-parameters and optimizer details are now logged automatically.
- Added new methods to get a single registry model item assets API.get_model_registry_version_assets() and download an Experiment or model registry item asset API.download_experiment_asset().
- Show a warning when a metric value is None and discarded.
Release 3.24.1¶
Release date: January 17, 2022
- Removed unnecessary warnings when using Pytorch and disabled experiments.
- Made sure all scikit-learn Estimator hyper-parameters are automatically logged.
Release 3.24.0¶
Release date: January 7, 2022
- Added APIExperiment.log_table() for logging tabular data from the APIExperiment. Includes logging data, CSV, TSV, JSON, MD and HTML file types.
Release 3.23.1¶
Release date: December 17, 2021
- When running in Google Colab environment, the whole notebook content is now logged when calling
Experiment.end()
. The content will be logged as the Experiment assetColabNotebook.ipynb
. - If
COMET_CONFIG
is set, this path will be used bycomet_ml.init()
,comet_ml.init_onprem()
andcomet_ml.save()
to save the file.
Release 3.23.0¶
Release date: November 26, 2021
- When creating a ExistingOfflineExperiment object, the resulting archive file name will now includes a random suffix, avoiding a potential overwriting if another file already exists.
- Allow to override workspace and/or project_name when uploading offline experiments with
comet upload
with the--workspace
and--project-name
CLI flag. Seecomet upload --help
for more information.
Release 3.22.1¶
Release date: November 19, 2021
- Added deprecation warning when using the Predictor. Predictor will be fully removed on February 2022.
- Fixed
comet check
to work on Windows platform.
Release 3.22.0¶
Release date: November 16, 2021
Release 3.21.0¶
Release date: November 6, 2021
- Experiment.get_name() now returns proper randomized name for Online experiments
- Added API.get_default_workspace()
- Added automatic logging for Google colab url
Release 3.20.0¶
Release date: November 2, 2021
- Fixed URL
comet_ml.init_onprem()
error - Images added via
tf.summary.image
should keep name - Fixed regression in setting api-key from CLI
comet upload
now returns a non-zero exit code if at least one experiment has failed to upload- Added Experiment.send_notification() example
Release 3.19.1¶
Release date: October 25, 2021
- Updated MLflow support
- Fixed an issue when setting COMET_DISPLAY_SUMMARY_LEVEL
- Updated Jupyter Code logging when calling Experiment.end()
Release 3.19.0¶
Release date: October 13, 2021
- Added
comet init --onprem
; see Comet Onprem User Instructions for more details - Added configurable prefix for CPU and GPU system metrics; See comet.distributed_node_identifier for more details
- Updated Optimizer docstring to better explain
experiment_class
parameter
Release 3.18.1¶
Release date: October 7, 2021
- Fixed loss metric logging by PyTorch logger; see PyTorch Examples for more details
- Noted that Python 3.5 requires websocket_server<0.5.4
Release 3.18.0¶
Release date: October 1, 2021
- Added support for the latest Scikit-Learn with new new
SplineTransformer
andPolynomialFeatures
estimators - Added a default value for offline directory
.cometml-runs/
that was prevously required whenever creating anOfflineExperiment
or anExistingOfflineExperiment
. If the default cannot be created or cannot be used due to permissions errors, a temporary directory will be used instead. The offline directory can be set either in the code by passing theoffline_directory
parameter on Experiment creation or through the configuration by setting thecomet.offline_directory
config key (COMET_OFFLINE_DIRECTORY
environment variable)
Release 3.17.0¶
Release date: September 27, 2021
- Fixed a potential memory-leak by removing a reference to the Pytorch Model whenever an Experiment ends or is cleaned
- Updated the command-line
comet check
to include more information about the environment
Release 3.16.0¶
Release date: September 16, 2021
- Improved TensorFlow 2.6 support
- Better alignment between the
API
class in the Python SDK and thePython Panels API - Hyperparameters are now stored with their fully-qualified name, including the current context (such as "train" and "test") at logging. For example, parameters logged with:
with experiment.train():
experiment.log_parameter("training_rate", 0.0001)
can be retrieved with:
experiment.get_parameter("train_training_rate")
# or:
with experiment.train():
experiment.get_parameter("training_rate")
Release 3.15.4¶
Release date: September 8, 2021
- Improved logging parameters using a batched-upload protocol over new queue system
Release 3.15.3¶
Release date: September 2, 2021
- Increased coverage of test matrix to include tensorflow 2.5
- Ensure that floating-point epochs are handled properly
Release 3.15.2¶
Release date: August 30, 2021
- Improve messages at experiment end when data is still uploading
- Update timeout for offline experiment uploading
- Resolved an issue with concurrent access to message queues
Release 3.15.1¶
Release date: August 26, 2021
- Restore compatibility with
jsonschema
2.6.0 for easy use on Google Colab - Improve offline experiment background uploading
Release 3.15.0¶
Release date: August 24, 2021
- Allow logging step as a floating-point value for file uploads; fixes Hugging Face's transformer issue
- When logging the git patch, it is now computed and logged in the background making
Experiment()
creations much faster. See Experiment(log_git_patch) for more details onlog_git_patch
- Logging an Artifact now fails if you try to add two assets with the same logical path
- Updated required
jsonschema
package version; fixes issue on Google Colab OfflineExperiment uploading - Increased the timeout for downloading experiment model zipfiles from 10s to 600s to match the timeout for downloading registered models
Release 3.14.0¶
Release date: August 6, 2021
- Fix API Key redaction in log messages when an invalid API Key is provided
- Add warnings when a Keras callback tries to log to a closed Experiment object
- Add
LoggedArtifact.get_asset
andLoggedArtifactAsset.download
method to get a single Artifact Asset and download it - Fix Artifact download
PRESERVE
strategy, file content could have been overwritten - Update log messages when an Experiment object finished to upload data before ending (either explictly or implicitly). The new log messages now includes the remaining size to upload, the estimated upload speed and an estimated time to completion
Release 3.13.2¶
Release date: July 28, 2021
- Fix required everett version for Python 3.5
- Fix a potential file leak
Release 3.13.1¶
Release date: July 12, 2021
- Fix a confusion matrix issue where
selected
was ignored overmax_categories
; for more information see Experiment.log_confusion_matrix() - Added LoggedArtifact.get_source_experiment() and LoggedArtifact.source_experiment_key
Release 3.13.0¶
Release date: July 12, 2021
- Added progress log messages to
Experiment.log_artifact()
- Increase default asset max size to 100Gb
- Added retries for file uploads
- Increased default parallel and max thread counts
Release 3.12.2¶
Release date: June 24, 2021
- Added enhancements for faster logging
- Fixed an issue with an internal histogram method,
Histogram.add(values, counts)
- Updated tab URL names; see Experiment.display(tab=NAME)
- Updated Comet system debugging tool; see see
comet check
Command-line interface - Included the optimizer total parallel job value in environment variable; see
comet optimize
Command-line interface - Enhanced artifact download speeds; see [Artifact Overview]/docs/v2/guides/artifacts/using-artifacts/#download-a-logged-artifact) for more information
Release 3.12.1¶
Release date: June 18, 2021
- Added better error reporting when there is an experiment creation failure
- Added support for
comet_ml.init(api_key=)
and more robust error handling; see Interactive Setup and Comet Command-Line Utilities for additional information - Enhanced support for Pytorch 1.9; see Pytorch and Pytorch Lightning for more information
- Allow multiple embeddings logged without having to name them; see Experiment.log_embedding()
- Added enhancements for uploading files faster
Release 3.12.0¶
Release date: June 7, 2021
- Enhanced
Experiment.get_artifact()
to track consumer experiments; see LoggedArtifact - Allow logging more than one embedding without explicit naming; see Experiment.log_embedding()
- Enhanced Experiment logging to track GPU temperature; see Experiment(log_env_gpu=True,log_env_details=True) and COMET_AUTO_LOG_ENV_GPU
Release 3.11.0¶
Release date: May 27, 2021
- Added support for Artifacts such as datasets; see Artifacts, and Experiment.log_artifact()
- Fixed an issue with APIExperiment.display()
- Added additional Confusion Matrix API enhancements for image examples; see Experiment.log_confusion_matrix()
Release 3.10.0¶
Release date: May 6, 2021
- Updated Confusion Matrix API for easily creating example images; see Confusion Matrix
- Enhanced messages for
comet init
code generator; see Command-line Utilities
Release 3.9.1¶
Release date: May 6, 2021
- Added better error reporting when attempting to register a model from an experiment with no models; see Experiment.log_model() and APIExperiment.register_model() for more information
- Comet Python SDK now requires an on-prem backend version 2.037 or greater
- Now avoids logging empty parameters for sklearn auto logging; see Experiment(auto_param_logging=True) and scikit-learn tutorial for more information
Release 3.9.0¶
Release date: April 15, 2021
- Allow logging 3D arrays as color images; see Experiment.log_image(image_shape=(width, height, colors))
- Revised
comet check
test for websockets; see Command-line comet check for more information - Revised Comet API key redaction in logs
Release 3.8.1¶
Release date: April 8, 2021
- Added support for the
NO_PROXY
environment variable - Added additional information on the required use of Experiment.end() when in Jupyter Notebook-based environments
Release 3.8.0¶
Release date: April 6, 2021
- Added support for pathlib in Experiment.log_image()
- Added support for logging Plotly figures using Experiment.log_figure(figure=)
- Refined APIExperiment.display(tab=) and Experiment.display(tab=) for opening specific tabs in the UI
Release 3.7.0¶
Release date: March 26, 2021
- Added
comet_ml.init()
andcomet init --api-key
for easy API key configuration in interactive environments; see Python Configuration and Comet Command-Line Utilities for additional information - Updated tests for lightgbm; see the lightgbm tutorial for more information on use with Comet
- Updated tests for pytorch-lightning; see the pytorch-lightning tutorial for more information on use with Comet
Release 3.6.0¶
Release date: March 18, 2021
- Hide the API key in logs; see
COMET_LOGGING_HIDE_API_KEY
in the Comet Configuration Variables. - Additional documentation for renaming, computing, or copying metrics
Release 3.5.0¶
Release date: March 12, 2021
- Removed netifaces from
comet_ml
Python SDK requirements - Added auto-logging for Facebook Prophet; see the Prophet Tutorial for more information
- Expose ExistingOfflineExperiment and
get_global_experiment
from toplevel comet_ml imports (e.g.,from comet_ml import ExistingOfflineExperiment
)
Release 3.4.0¶
Release date: March 4, 2021
- Added ability to not log the folder names on model logging. See Experiment.log_model(prepend_folder_name=False) for more information.
Release 3.3.5¶
Release date: February 26, 2021
- Fixed a repeating warning when logging an empty dict of parameters
- Fixed a command-line argument parse bug
Release 3.3.4¶
Release date: February 18, 2021
- Avoids double-logging of source code with Python 3.9; see Experiment(log_code=True) and Experiment.log_code()
- Added warning messages when trying to log an empty parameters dictionary; see Experiment.log_parameters()
- Added more detailed logs when waiting for data to be uploaded at end of
Experiment()
Release 3.3.3¶
Release date: February 11, 2021
- Increased asset upload timeouts in the Python SDK to better handle large files and slow connections
- Enhanced
Experiment.log_remote_asset()
remote file name; see Experiment.log_remote_asset() - Enhanced
Experiment.log_table()
documentation; see Experiment.log_table() - Fixed
API.get_experiment_by_id(ID)
to return None when ID does not exist; see API.get_experiment_by_id() - Refinements to
comet offline
; see Command-line API - Added Python 3.9 to our extensive internal test matrix
Release 3.3.2¶
Release date: February 4, 2021
- Fixed an issue in rendering logged figures, including SHAP figures, in the UI
- Additional refinements for better logging Jupyter Notebook source code
Release 3.3.1¶
Release date: February 2, 2021
- Fixed a bug in
experiment.end()
, a required call in Jupyter notebooks, and optional in other scenarios. CallingExperiment.end()
fails with version 3.3.0. See Experiment.end() for more information.
Release 3.3.0¶
Release date: February 1, 2021
- This version of the Comet Python SDK uses a new Comet Optimizer that has many bug fixes and enhancements. See Optimizer for more details on using the Optimizer
- Added remote asset logging. Useful for tracking remote or local files that you may not wish to upload but want to track. See Experiment.log_remote_asset()
- Log multiple source files. Useful for when your experiment code is spread across multiple files, or the top-level Python script is not where
Experiment()
is called. TheExperiment.log_code()
function is also enhanced to log source code that was missed in prior versions. See Experiment.log_code() - Added auto-logging support for TensorFlow Estimators. Now logs model definition, .pbtxt model file, and hyperparameters in addition to metrics. See TensorFlow Estimator Integration
- Added support for huuuge asset file uploads. See Experiment.log_asset() and related functions
Release 3.2.12¶
Release date: January 21, 2021
- Use "simple" for
auto_output_logging
rather than "default" or "native" on MacOS. This is a temporary solution to address an issue with Python 3.8 and greater on Darwin. See Experiment() for more details onauto_output_logging
.
Release 3.2.11¶
Release date: January 14, 2021
- Added support for logging 3D point cloud and bounding boxes; see Experiment.log_points_3d()
- Altered logging configuration to improve performance
Release 3.2.10¶
Release date: January 7, 2021
- Adding tags will retry in case of connection errors; see Experiment.add_tag() and Experiment.add_tags()
- Fixed uploading of non-UTF-8 data issue
Release 3.2.9¶
Release date: December 18, 2020
- New Experiment.log_code() for logging additional source code files and folders
- Allow downloading latest version of model without specifying stage; see API.download_registry_model()
- Expanded auto-logging for sklearn >=0.22
- Updated internal check for live threads for latest Python 3.9
- Updates for pytorch_lightning code logging
Release 3.2.8¶
Release date: December 8, 2020
- Added SHAP auto-logging
Release 3.2.7¶
Release date: December 2, 2020
- Added lightgbm auto-logger
- Fixed an XGBoost callback issue
Release 3.2.6¶
Release date: November 23, 2020
- Added ExistingOfflineExperiment for continuing an experiment in offline mode
- Added Experiment.log_dataframe_profile()
- Extended Experiment.log_table() to be able to log a Pandas DataFrame
- Added ability for the
comet_ml
Keras auto-logger to log gradient and activation histograms in addition to weight histograms - Added ability for comet_ml to run if the
pynvml
package is deleted or doesn't install properly (thanks to the Ludwig team for tracking down issue)
Release 3.2.5¶
Release date: October 26, 2020
- Added support for auto-logging TensorFlow Model Analysis results
Release 3.2.4¶
Release date: October 12, 2020
- Added Hydra config logging (thanks to Vozf)
- Added environment query variable
- Matplotlib's save doesn't flush stream (thanks to jliu)
Release 3.2.3¶
Release date: October 5, 2020
- Fixed
comet models
with Python 3 - Accept unknown from backend query variables
- Added additional Confusion Matrix error logging
- Enhanced index_to_example for Confusion Matrix creation
- Enhanced Pytorch AMP Support
- Allow logging epochs to be floating point values; used by HuggingFace Transformers
Release 3.2.2¶
Release date: September 22, 2020
- Expanded Confusion Matrix to work with integer-based labeled y_true, rather than requiring onehot vectors: see Experiment.log_confusion_matrix() for more information.
- Allow Torch tensors attached to a gradient to work throughout comet_ml (including confusion matrix, histogram logging, etc)
Release 3.2.1¶
Release date: September 18, 2020
- Fixed a confusion matrix issue with non-integer indices (thanks ironcadiz for reporting)
- Refactored and expanded xgboost auto-logging
- Added output refinements when running experiments (reduced duplicated messages, better messages, etc.)
- Fallback to
tf.keras
ifkeras
is not installed (thanks DN6 for reporting) - Replaced comet-git-pure with dulwich
Release 3.2.0¶
Release date: August 28, 2020
- Added major speed-up for logging histograms
- About 10 times faster when used with numpy
- Added refinements for logging metrics with xgboost
- Added refinements for the [Predictive Early Stopping]
- Added refinements for logging parameters, others, and metrics (thanks for reporting @Idodox!)
- Added better representations of dictionaries and other objects
- Added warning if key or value is truncated
- Dropped support for Python 3.4
Release 3.1.17¶
Release date: August 20, 2020
This release will be the last to support Python 3.4.
- Fixed issue to allow
COMET_AUTO_LOG_DISABLE
to disable allcomet_ml
actions. For more information, see Experiment Configuration Parameters. - Fixed issues using
comet_ml
on Google Colab that required restarting Colab engine:- Can now use Colab's default version of
jsonschema
comet upload
failed without restart
- Can now use Colab's default version of
Release 3.1.16¶
Release date: August 6, 2020
- Refined Experiment(auto_weight_logging=True) for Keras:
- creates separate 3D histograms for weight matrices and bias arrays
- uses layer names for Histogram names
- Added Histogram and image processing speed ups (up to 10x faster)
- Added more flexible logging of parameters
- Added more flexible source code logging for Experiment(log_code=True)
Release 3.1.15¶
Release date: August 3, 2020
- Configurable Experiment arguments. You can now control all of the auto-logged Experiment parameters from your Comet config settings (environment, code, or config file)
- Better logging of model graph representation (can record JSON, yaml, and string representations). Occurs automatically with
Experiment(log_code=True)
or withCOMET_AUTO_LOG_CODE
. - Better logging of source code (can better find source code when using
ludwig
ortransformers
) - Added additional APIExperiment methods: APIExperiment.log_parameters(), and APIExperiment.log_metrics()
- Fixed Comet Optimizer document examples
- Confusion matrix optimization: if Experiment.log_confusion(..., selected=[...]) and
index_to_example_function
given, only make those examples selected - Added username to experiment metadata. See APIExperiment.get_metadata()
Release 3.1.14¶
Release date: July 21, 2020
- Added support for keras automatic weight and bias logging as a 3D histogram, see Experiment(auto_weight_logging=True)
Release 3.1.13¶
Release date: July 17, 2020
- Added support for pytorch apex, online-pytorch-lightning-apex-example.py
- Documented metadata for many Experiment methods
- Added new methods APIExperiment.get_curve(), and APIExperiment.get_curves() with step
- Added API.get_project_share_keys(), API.create_project_share_key(), and API.delete_project_share_key() for programmatically sharing projects
- Limited backend handshake message to only show once
- Changed some conversion warnings to debug level
- Added new file download timeout config for downloading assets,
COMET_TIMEOUT_FILE_DOWNLOAD
Release 3.1.12¶
Release date: June 25, 2020
- Add partial support for using the Optimizer with the Pytorch Lightning Comet Logger. See here for an example.
- Add
experiment.display_project
for all kinds of experiments (online, offline and api). Behavior is similar toexpriment.display
. - Add file download timeout configuration,
COMET_TIMEOUT_FILE_DOWNLOAD
with a default value of 600 seconds. This is used only for registry downloading at the moment.
Release 3.1.11¶
Release date: June 17, 2020
- Better logging of all kind of summary data when using
tensorflow.summary
. - Added better error catching in Keras callbacks.
Release 3.1.10¶
Release date: June 9, 2020
- Added
comet models download
andcomet models list
commands, seecomet models
- Added
comet init
command to generate example scripts from cookiecutter recipe, seecomet init
- Removed dependency on
typing_extensions
to allow%pip install comet_ml
to work with Google Colab without a kernel restart
Release 3.1.9¶
Release date: June 6, 2020
- Added Experiment.log_embedding()
- Added Experiment.log_table()
- IPython environments now log code, output, and Code.ipynb
- Added
comet check --debug
command, seecomet check
- Added custom context manager,
with experiment.context_manager(CONTEXT)
- Added support for downloading a model based on its stage, see API.download_registry_model()
- Increased file upload timeout to 15 minutes
Release 3.1.8¶
Release date: May 26, 2020
- Improvements to work better on Google Colab
- Added API.move_experiments()
- Restored ability to
from comet_ml import get_global_experiment
Release 3.1.7¶
Release date: May 18, 2020
- Refined APIExperiment.display()
- Made HTTP timeouts configurable. See
COMET_TIMEOUT_HTTP
- Display a log message when an experiment has been throttled
- Fixed support for Python 2.7 in conda package
- Added new auto-logger for XGBoost
- Added ability to fetch parameters with API.get_metrics_for_chart()
- Better invalid model name message: shows possible valid names
Release 3.1.6¶
Release date: April 20, 2020
- Fixed documentation for
ExistingExperiment()
default parameters - Fixed console logging that was cut off
- Added auto-logged cloud metadata (currently AWS, Azure and Google Cloud Platform are supported)
- Added error checking for
API.get_metrics_for_chart()
- Added
Histogram.from_json()
and default args forhistogram.display()
Release 3.1.5¶
Release date: April 14, 2020
- Fixed empty Experiment Summary section headings from showing
- Updated conda's comet_ml dependencies to match pip's comet_ml dependencies
- Fixed reading non-utf8 Unix package descriptions
- Fixed Experiment's
disabled
parameter docstrings - Fixed APIExperiment.set_os() docstrings
Release 3.1.4¶
Release date: April 7, 2020
- Added support for deleting assets from the Python API:
- Added support for setting code from a filename:
- Enhanced Experiment Summary:
- Now shows parameters logged
- Control with
display_summary_level
(display_summary
is now deprecated):- Experiment(display_summary_level=LEVEL)
display_summary_level=0
: display nothingdisplay_summary_level=1
: display metrics, parameters, and upload counts and sizesdisplay_summary_level=2
: everything at level 1, plus system metrics
- Added new method APIExperiment.archive()
- Added checks to prevent logging empty 3D histograms
Release 3.1.3¶
Release date: March 23, 2020
- Ability to control the git directories; see COMET_GIT_DIRECTORY
- Added Experiment.log_curve() and APIExperiment.log_curve()
- Added ability to assign resources per parallel instance when running
comet optimizer
; see COMET_OPTIMIZER_PROCESS_ID - Added Experiment.get_name() and APIExperiment.get_name()
- Many enhancements and speedups
Release 3.1.2¶
Release date: March 12, 2020
- Deprecated
COMET_REST_API_KEY
in Python API; just useCOMET_API_KEY
now - Noted the correct minimum psutil version (5.6.3) in setup.py
- Fixed issue with auto output logging in
OfflineExperiments
from Jupyter - Fixed Keras and Tensorflow model graphs to produce diff-able representations
Release 3.1.1¶
Release date: February 27, 2020
- Added experiment model and registry model support to API, see Guides / Manage Models
- Added ability to properly set project notes to unicode in Python 2, see API.set_project_notes()
Release 3.1.0¶
Release date: February 17, 2020
- Added MLflow auto-logging
- Released a Python universal wheel (available using pip) to improve Python 2 installation speed
- Fixed some logging methods that were not respecting Experiment.disabled when True
Release 3.0.3¶
Release date: February 10, 2020
- Added Experiment.log_asset_folder() folder name
- Added API.get_account_details()
- Added logs errors to
OfflineExperiment
- Added Read/write project notes to Python API
- Added
API.server_url
property - Fixed Comet CLI for Python 2; added comet --version
- Added
Experiment.log_model()
, APIExperiment.download_model() and APIExperiment.get_model_names() - Added logging for
optimizer_objective
; use proper JSON for optimizer parameters logging - Fixed convert_to_scalar to handle numpy type
- Ensure
comet optimize
exits with a non-zero exit code if a child exit with an error - Stopped sending sample_rate as metadata when logging an audio file
Release 3.0.2¶
Release date: December 19, 2019
- Added optional metadata to all
Experiment.log_asset_data()
methods - Added 'text' to
Experiment.display(tab='text')
- Updated automatic logging docstrings (thanks to lemairecarl for suggestion)
- Added
Experiment.log_text()
- Added ability to stop a running experiment from Python API
- Added license information
Release 3.0.1¶
Release date: December 10, 2019
- Added Experiment.log_confusion_matrix()
- Added
Experiment.display(TABNAME)
to open browser to Comet tab - Activated Keras and tensorflow.keras progress bars in console
Release 3.0.0¶
Release date: November 3, 2019
- Released REST v2 read and write endpoints
- Released updated Python API and updated APIExperiment
- Dramatically increased speed of Python API by using REST v2
- Added many additional Python API methods (update projects, delete projects, restore experiments, etc)
- Standardized Python API JSON field names to camelCaseNaming
- Added much more documentation and examples for Python API
- Brought APIExperiment inline with
Experiment
,OfflineExperiment
, andExistingExperiment
. Examples:- Create an experiment:
APIExperiment(workspace=WORKSPACE", project_name=PROJECT_NAME)
- Use an existing experiment:
APIExperiment(previous_experiment=EXPERIMENT_ID | NAME)
- Create an experiment:
- Added ability for all aspects of an experiment to be downloaded and changed from the Python API
- New and updated
API
methods:- API.clear_cache()
- API.create_project(WORKSPACE, PROJECT_NAME, [PROJECT_DESCRIPTION, PUBLIC])
- API.delete_project(workspace=WORKSPACE, project_name=PROJECT_NAME, delete_experiments=False)
- API.delete_project(workspace=WORKSPACE, project_id=PROJECT_ID, delete_experiments=False)
- API.get_project(WORKSPACE, PROJECT_NAME)
- API.get_project_by_id(PROJECT_ID)
- API.restore_experiment(EXPERIMENT_ID)
- API.update_project(WORKSPACE, PROJECT_NAME, [NEW_PROJECT_NAME, DESCRIPTION, PUBLIC])
- API.update_project_by_id(PROJECT_ID, [NEW_PROJECT_NAME, DESCRIPTION, PUBLIC])
- API.use_cache(True | False)
- New and updated
APIExperiment
methods:- New and updated read methods:
- APIExperiment.get_additional_system_info()
- APIExperiment.get_command()
- APIExperiment.get_executable()
- APIExperiment.get_gpu_static_info()
- APIExperiment.get_hostname()
- APIExperiment.get_ip()
- APIExperiment.get_max_memory()
- APIExperiment.get_network_interface_ips()
- APIExperiment.get_os()
- APIExperiment.get_os_type()
- APIExperiment.get_pid()
- APIExperiment.get_python_version()
- APIExperiment.get_python_version_verbose()
- APIExperiment.get_system_details()
- APIExperiment.get_system_metric_names()
- APIExperiment.get_tags()
- APIExperiment.get_total_memory()
- APIExperiment.get_user()
- New and updated write methods:
- APIExperiment.log_additional_system_info(KEY, VALUE)
- APIExperiment.log_asset(FILENAME, [STEP, OVERWRITE, CONTEXT, FTYPE, METADATA])
- APIExperiment.log_cpu_metrics(CPU_METRICS, [CONTEXT, STEP, EPOCH, TIMESTAMP])
- APIExperiment.log_gpu_metrics(GPU_METRICS)
- APIExperiment.log_html(HTML, [CLEAR, TIMESTAMP])
- APIExperiment.log_image(FILENAME, [IMAGE_NAME, STEP, OVERWRITE, CONTEXT])
- APIExperiment.log_load_metrics(LOAD_AVG, [CONTEXT, STEP, EPOCH, TIMESTAMP])
- APIExperiment.log_metric(METRIC, VALUE, [STEP, TIMESTAMP])
- APIExperiment.log_other(KEY, VALUE, [TIMESTAMP])
- APIExperiment.log_output(LINES, [CONTEXT, STDERR, TIMESTAMP])
- APIExperiment.log_parameter(PARAMETER, VALUE, [STEP, TIMESTAMP])
- APIExperiment.log_ram_metrics(TOTAL_RAM, USED_RAM, [CONTEXT, STEP, EPOCH, TIMESTAMP])
- APIExperiment.set_code(CODE)
- APIExperiment.set_command(COMMAND_ARGS_LIST)
- APIExperiment.set_end_time(TIME_MILLISECONDS)
- APIExperiment.set_executable(EXECUTABLE)
- APIExperiment.set_git_metadata(USER, ROOT, BRANCH, PARENT, ORIGIN)
- APIExperiment.set_git_patch(FILE_DATA)
- APIExperiment.set_gpu_static_info(GPU_STATIC_INFO)
- APIExperiment.set_hostname(HOSTNAME)
- APIExperiment.set_installed_packages(INSTALLED_PACKAGES)
- APIExperiment.set_ip(IP)
- APIExperiment.set_network_interface_ips(IPS)
- APIExperiment.set_os(OS)
- APIExperiment.set_os_type(OS_TYPE)
- APIExperiment.set_pid(PID)
- APIExperiment.set_python_version(PYTHON_VERSION)
- APIExperiment.set_python_version_verbose(PYTHON_VERSION_VERBOSE)
- APIExperiment.set_start_time(TIME_MILLISECONDS)
- APIExperiment.set_user(USER)
- New and updated read methods:
For more information on the Python API, see:
Release 2.0.18¶
Release date: November 22, 2019
- Fixed issue when creating multiple experiments sequentially
- Added ability for
Experiment.log_asset_folder()
to log files recursively with file names - Better handling of logging files and file-like objects
- Added ability for users to control auto logging details
Release 2.0.17¶
Release date: November 7, 2019
- Fixed a file-descriptor leak with native console logging
- Fixed
Experiment.log_figure()
to more accurately check for empty figures - Added
psutil
to conda dependencies
Release 2.0.16¶
Release date: October 29, 2019
- Corrected the offline file upload to have the right file extension
- Fixed logging an empty CPU load avg metric
- Fixed optional dependency declaration for the cpu logging feature. You can now use
pip install comet_ml[cpu_logging]
to install psutil. - Fixed a bug in
OfflineExperiment
that removed a file from disk when passingcopy_to_tmp=False
. - Improved file extension handling when uploading file with
OfflineExperiment
.
Release 2.0.15¶
Release date: October 16, 2019
- Added optional timestamp (in seconds) to Python
APIExperiment
:APIExperiment.log_other(..., timestamp=SECONDS)
APIExperiment.log_metric(..., timestamp=SECONDS)
APIExperiment.log_parameter(..., timestamp=SECONDS)
APIExperiment.log_html(..., timestamp=SECONDS)
APIExperiment.log_output(..., timestamp=SECONDS)
- Sped up
Experiment.end()
andOfflineExperiment.end()
- Pinned
jsonschema
to a Python 3.4 compatible version
Release 2.0.14¶
Release date: October 2, 2019
- Refactored Python API
- Added Query API
- Added CPU logging
- requires
psutil
(see above)
- requires
- Deprecated passing experiment keyword arguments to
Optimizer()
; now pass usingOptimizer.get_experiments(**kwargs)
Release 2.0.13¶
Release date: September 16, 2019
- Fixed repeated keras model unable-to-log warnings
- Fixed wrong context in keras callback
Callback.on_test_*()
methods; wastest
nowvalidate
Experiment.log_histogram_3d(values, step)
gives required-step error earlier
Release 2.0.12¶
Release date: September 4, 2019
- Added support for TensorFlow v2 for tensorflow>=1.14, and tensorflow==2.0
- Fixed a bug that was using
auto_param_logging
instead ofauto_metric_logging
to control tensorboard metric logging. - Added
Experiment.log_histogram_3d()
for logging time-series histograms.
Release 2.0.11¶
Release date: August 29, 2019
- Redefined valid experiment key (key must be alphanumeric, 32 to 50 characters)
Release 2.0.10¶
Release date: August 26, 2019
- Added support for all versions of TensorFlow v1 (1.11 - 2.0)
- Added
Experiment.get_callback("tf-keras")
- Fixed spelling errors in messages, comments, and code
- Removed reporting when websocket connection was closed on normal shutdown
Release 2.0.9¶
Release date: August 21, 2019
- Fixed GPU schema to report usage better
- Added
API.add_tags(experiment, tags)
- Fixed offline image upload issue
- Fixed sklearn to respect auto_param_logging flag
- Fixed SOCK HTTP Proxy which required an int port number
Release 2.0.8¶
Release date: August 14, 2019
- Added
{user}
to configurable logging file name patterns - Added
comet offline
to explore offline experiment ZIP files - Added
API.get_experiments()
andAPI.get_experiment()
- Added -m flag to
comet python
- Added COMET_EXPERIMENT_KEY for new experiments
Release 2.0.7¶
Release date: August 13, 2019
- Added
COMET_WORKSPACE
to the config - Added
COMET_CONSOLE
to set the console log level and display tracebacks - Added
COMET_LOGGING_FILE
name patterns, like "comet-{project}.log" - Added
Experiment.set_epoch(NUMBER)
- Added
Experiment.log_others({...})
- Fixed summary metric count
- Deprecated
Experiment.get_keras_callback()
; useExperiment.get_callback("keras")
Release 2.0.6¶
Release date: August 5, 2019
- Added step parameter to all asset logging methods
- Added
Experiment(disable_summary=True)
to disable display summary - Added a log message when an optimizer search has completed
- Added
comet python
CLI to automatically import Comet first - Fixed send_notification compatibility with older backend
- Added conda packaging support
Release 2.0.5¶
Release date: July 18, 2019
- Added step parameter to
Experiment.log_audio()
- Added
Experiment.send_notification()
Release 2.0.4¶
Release date: July 15, 2019
- Added base64-encoded metadata in the log_audio call
Release 2.0.3¶
Release date: July 15, 2019
- Added support for
Experiment.log_audio()
- Added
comet_ml.config.save()
- File upload now sends file extension
Release 2.0.2¶
Release date: July 2, 2019
- Added support for logging binary assets with
Experiment.log_asset_data()
- Added more hook-points for tensorboard auto logging
Release 2.0.1¶
Release date: June 20, 2019
- Fixed tensorflow context logging for Tensorflow >1.13.1
Release 2.0.0¶
Release date: June 18, 2019
- Added a log message when an experiment was created offline
- Added a log message when an experiment was stopped
- Improved stop message
- Removed deprecated methods, this makes this release not backward compatible
- Added a new Optimizer which breaks the older API
- Added new tensorflow hooks to set the context properly
Release 1.0.56¶
Release date: June 5, 2019
- Updated
OfflineExperiment()
to accept the same API arguments asExperiment()