Mlflow integration callback (#8016)

* Add MLflow integration class

Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.

* Add MLflowCallback import

Add import of MLflowCallback in trainer.py

* Handle model argument

Allow the callback to handle model argument and store model config items as hyperparameters.

* Log parameters to MLflow in batches

MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.

* Fix style

* Add docs on MLflow callback

* Fix issue with unfinished runs

The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.

* Add MLflow integration class

Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.

* Add MLflowCallback import

Add import of MLflowCallback in trainer.py

* Handle model argument

Allow the callback to handle model argument and store model config items as hyperparameters.

* Log parameters to MLflow in batches

MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.

* Fix style

* Add docs on MLflow callback

* Fix issue with unfinished runs

The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.
This commit is contained in:
noise-field
2020-10-26 16:41:58 +03:00
committed by GitHub
parent 8be9cb0aef
commit c48b16b8da
3 changed files with 99 additions and 0 deletions

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@@ -20,6 +20,7 @@ By default a :class:`~transformers.Trainer` will use the following callbacks:
or tensorboardX).
- :class:`~transformers.integrations.WandbCallback` if `wandb <https://www.wandb.com/>`__ is installed.
- :class:`~transformers.integrations.CometCallback` if `comet_ml <https://www.comet.ml/site/>`__ is installed.
- :class:`~transformers.integrations.MLflowCallback` if `mlflow <https://www.mlflow.org/>`__ is installed.
The main class that implements callbacks is :class:`~transformers.TrainerCallback`. It gets the
:class:`~transformers.TrainingArguments` used to instantiate the :class:`~transformers.Trainer`, can access that
@@ -46,6 +47,9 @@ Here is the list of the available :class:`~transformers.TrainerCallback` in the
.. autoclass:: transformers.integrations.WandbCallback
:members: setup
.. autoclass:: transformers.integrations.MLflowCallback
:members: setup
TrainerCallback
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~