Lambda wrapper callback

[elephantmipt]

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Description

Related Issue

Type of Change

• Examples / docs / tutorials / contributors update
• Bug fix (non-breaking change which fixes an issue)
• Improvement (non-breaking change which improves an existing feature)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

PR review

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PS

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[pep8speaks]

Hello @elephantmipt! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2021-04-15 15:21:04 UTC

[Scitator]

btw, could you please also add this callback usage to the test and examples?

• ML - multilabel classification
• https://github.com/catalyst-team/catalyst/blob/master/catalyst/tests/test_multilabel_classification.py#L36

[mergify]

This pull request is now in conflicts. @elephantmipt, could you fix it? 🙏

[Scitator]

could we simplify the code a bit?
ley's support only 2 cases:

1. tuple-in, tuple-out, specified with input_key, output_key, for example:

• input_key=logits, output_key=scores
• input_key=["logits", "weights"], output_key=scores
• input_key=emgeddings, output_key=["pos_embeddings", "neg_embeddings"]

in this case, could simply use:

def batch_handler(self, runner):
    batch_in = [runner.batch[key] for key in self.input_key]
    batch_out = self.handler(batch_in)
    runner.batch.update(**{key:value for key, value in zip(self.output_key, batch_out)})

2. dict-in, dict-out, specified with input_key=None, output_key=None
   usage:

def batch_handler(self, runner):
    runner.batch = self.handler(runner.batch)

Pull request has been modified.

Pull request has been modified.

Pull request has been modified.