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Callbacks neptune #491

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- What I did
Added a training callback for Neptune integration.
Supports automatic logging of keras train/val losses and metrics, as well as arbitrary parameter/tag/attribute logging.

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- How I did it
I subclassed the keras.callbacks.Callback class and made it write the on_epoch_end logs as neptune metrics.
The parameter/tag/attribute logging is simply by forwarding the keyword arguments to the neptune.projects.Project.create_experiment method.

- How you can verify it
Currently you can only verify it by running the example provided.
This is because Neptune requires a registered account and API token.

- Request for comments

  • Should we require users to use the environment variable NEPTUNE_API_TOKEN rather than having the option to supply it? The motivation is to prevent users accidentally sharing their private keys.
  • Is an example sufficient in lieu of a unit test? We cannot write a unit test without revealing a user account or API token.

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