Mlflow integration callback#8016
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LysandreJik merged 15 commits intohuggingface:masterfrom Oct 26, 2020
noise-field:mlflow-integration-callback
Merged
Mlflow integration callback#8016LysandreJik merged 15 commits intohuggingface:masterfrom noise-field:mlflow-integration-callback
LysandreJik merged 15 commits intohuggingface:masterfrom
noise-field:mlflow-integration-callback
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Add integration code for MLflow in integrations.py along with the code that checks that MLflow is installed.
Add import of MLflowCallback in trainer.py
Allow the callback to handle model argument and store model config items as hyperparameters.
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.
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 integration code for MLflow in integrations.py along with the code that checks that MLflow is installed.
Add import of MLflowCallback in trainer.py
Allow the callback to handle model argument and store model config items as hyperparameters.
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.
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.
…e-field/transformers into mlflow-integration-callback
sgugger
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Oct 26, 2020
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This is very clean, thanks a lot for this PR!
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What does this PR do?
This PR adds Trainer integration with MLflow.
It is implemented in roughly the same way as other integration callbacks (CometML, wandb) and gets added to the list of Trainer callbacks automatically when mlflow is installed. All the mlflow parameters are configured with env variables, as described in the library documentation. This PR adds an additional environment variable,
HF_MLFLOW_LOG_ARTIFACTS, which controls whether to use mlflow artifact logging facility to save artifacts generated after training (it doesn't make much sense if mlflow is used locally).Fixes #7698
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@sgugger