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support lr_scale to support scaled LR in head modules #569

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Summary:
For fine-tuning xrayvideo 2019a model, we want to use small LR for trunk which is already pre-trained, and larger LR for heads which are randomly initialized.
Thus, we store parameters from heads (and losses) in a separate parameter group, which use a lr_scale larger than default 1.0.

Differential Revision: D22618972

Differential Revision: D21949491

fbshipit-source-id: 1fb62f0280553cbbdf7194cbe857086fb9bb765e
Differential Revision: D22372256

fbshipit-source-id: a986a1f150374ef535b40e850f2c49a2fe780ac4
Differential Revision: D22618966

fbshipit-source-id: 294a9a23f4777601bdf577cdce61a086b167f61e
Summary:
For fine-tuning xrayvideo 2019a model, we want to use small LR for trunk which is already pre-trained, and larger LR for heads which are randomly initialized.
Thus, we store parameters from heads (and losses) in a separate parameter group, which use a `lr_scale` larger than default 1.0.

Differential Revision: D22618972

fbshipit-source-id: 1011cff648761f3c9fc3e6b370b773799ca78296
@facebook-github-bot facebook-github-bot added CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. fb-exported labels Jul 19, 2020
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This pull request was exported from Phabricator. Differential Revision: D22618972

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