PyPI v0.13.3

Features and Bug Fixes

• Add binding for tensorboard.summarywriter.addscalars
• Add Logger.tensorboard_single_series_per_graph() configuration option to allow per-series TensorBoard-like graphs
• Add docker image interface using Task.set_base_docker() and Task.get_base_docker()
• Use standard OS environment variables to obtain default credentials for:
  • AWS: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and AWS_DEFAULT_REGION
  • Azure: AZURE_STORAGE_ACCOUNT and AZURE_STORAGE_KEY
  • Google: GOOGLE_APPLICATION_CREDENTIALS
• Add simple dictionary task parameters interface using Task.get_parameters_as_dict() and Task.set_parameters_as_dict() allowing getting and setting parameters for task instances obtained using Task.get_task()
• Make sure Task.connect() always returns the connected instance passed to it
• Prefer tensorflow_gpu over tensorflow when inspecting installed packages and recording experiment dependencies
• Remove title/series naming restrictions (allow $ and .) when reporting metrics
• Fix incorrect printouts in initialization wizard and upgrade notifications
• Fix debug images URL for uploaded files with % in their name

Breaking Changes

• Rename trains.debugging.apply_args() to trains.debugging.apply_logging_args()

PyPI v0.13.2

Features and Bug Fixes

• Allow reporting a pre-uploaded image url in Logger.report_image() using the url parameter
• Add support for git repositories without ".git" suffix (e.g. Azure Repos)
• Improve conda support
• Improve hyper-parameters argparser integration
• Fix savefig() patching in matplotlib binding
• Fix logs, events and jupyter flushing on exit

PyPI v0.13.1

Features and Bug Fixes

• Add support for pyplot.savefig and pylab.savefig in matplotlib binding
• Add support for SageMaker
• Improve configuration wizard
• Try to make sure tensorboard is available when using torch
• Do not store keras model network design if it cannot be serialized #72
• Fix matplotlib binding support

PyPI v0.13.0

Features and Bug Fixes

• Add support for trains-server v0.13.0
• Add support for nested (non-main) tasks
• Add warning when automatic argument parser binding cannot be turned off
• Add Task.upload_artifact() support for external URLs (pre-uploaded)
• Add support for special characters in hyper-parameter keys (white-spaces, . and $) #69
• Add support for PyTorch .pt model files
• Calculate data-audit artifact uniqueness by user-criteria #45
• Use an environment variable for setting a default docker image #58
• Improve trains-init configuration wizard
• Update examples for new joblib versions
• Update jupyter example to TensorFlow 2
• Fix task clone to copy only input artifacts
• Fix matplotlib import binding when using Agg backend
• Fix ProxyDictPreWrite and ProxyDictPostWrite so they can be pickled correctly #72
• Fix requests issue in Python 2.7 that can cause a deadlock when importing netrc
• Fix argparser binding sub-parser and type casting support #74
• Fix argparser binding python 2.7 unicode handling
• Fix unsynced connected hyper parameters overridden during remote execution

PyPI v0.12.2

Features and Bug Fixes

• Add default_output_uri feature #57
• Improve trains-init configuration wizard
• Improve argparser binding
• Fix artifact support in data pipeline #63
• Fix threading issue while querying multiple experiments #64
• Fix uploading large files over slow HTTP connections
• Fix support for Git versions < 2

Breaking Changes

• Do not reuse an experiment with artifacts

PyPI v0.12.1

Features and Bug Fixes

• Add Task.connect_configuration(), connect your configuration file (or configuration dictionary including nesting support). See example.
• Add Task.connect_label_enumeration(), store model detection classes together with the model & experiment
• Edit & override configuration file (or dictionary) content when executing with trains-agent
• Task.connect() automatically supports nested dictionaries (e.g. param/nested/key) , including overriding values when running with trains-agent. See example.
• Add Artifact.get(), download & load an artifact.
• Add Task.get_tasks(), retrieve previous experiments, get metrics, rename etc.
• Improve Windows support
• Improve Minio support
• Fix Python2 support
• Fix Issue #56

PyPI v0.12.0

Features and Bug Fixes

• TRAINS Agent support (Full DevOps support)
• Add AutoML and orchestration examples
  Supports TRAINS-server v0.12 or above
• Add Logger x/y/z axis title for: report_surface / report_confusion_matrix / report_scatter3d / report_scatter2d / report_histogram
• Add support for TensorFlow 2.0
• Embed pyhocon into package
• Fix artifacts support on Windows
• Fix example code Windows support

PyPI v0.11.3

Features and Bug Fixes

• Resource-Monitor will only monitor active GPU devices
  based on environment variables: NVIDIA_VISIBLE_DEVICES or CUDA_VISIBLE_DEVICES
• Fix issue #48

PyPI v0.11.2

Features and Bug Fixes

• Fix Python 2.7 support
• Improve sample code Windows support

PyPI v0.11.1

Features and Bug Fixes

• GPU Monitoring is now embedded into trains (removed gpustat dependency)
• Add initial support for Tensorflow v2.0 (tested with v2.0.0rc1)
• Add artifact upload retry on network errors (default: 3)
• Suppress urllib3 retry warnings
• Fix Matplotlib support with Agg backend (multiple plot windows caused repeated graphs to be sent)
• Fix support for tuples in hyper-parameters
• Fix multi processing issues with different task types