Hiddens modules bugfixes #8466
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Hiddens modules bugfixes #8466
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michalivne
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LGTM! Fantastic PR, great catch of multiple issues.
I have a couple more suggestions to add to PR:
- Currently reconstruction loss mixes between samples in the batch. We should fix that.
- Add support in sample-level (not token level recon.) - token level should average iver hidden_size as well.
- Add support in scaling only gradients.
nemo/collections/nlp/models/language_modeling/megatron_lm_encoder_decoder_model.py
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nemo/collections/nlp/models/language_modeling/megatron_lm_encoder_decoder_model.py
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nemo/collections/nlp/modules/common/megatron/hiddens/megatron_hiddens.py
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nemo/collections/nlp/modules/common/megatron/hiddens/megatron_hiddens.py
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nemo/collections/nlp/modules/common/megatron/hiddens/megatron_hiddens.py
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nemo/collections/nlp/modules/common/megatron/hiddens/megatron_hidden_loss.py
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… time. Signed-off-by: John St John <jstjohn@nvidia.com>
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This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days. |
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I need to get back to this.
…On Wed, Mar 20, 2024 at 6:44 PM github-actions[bot] < ***@***.***> wrote:
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What does this PR do ?
Hiddens modules such as
a_mimandvaeoutput a number of keys, including{"z", "z_mean"}for example. The current implementation supports specifying a single key to be used as the encoder output, and generally in configs this is set tozfor those variational losses. This is not what you expect at inference time though. In that case you want the latent space to be a point estimate (the mean) rather than a noisy sampling. This PR accomplishes this by adding an optional second encoder output key to be used at inference time, and if it is not set then the current key is used for both. Inference/training is determined by checking the pytorch module propertyself.training.Collection: nlp
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