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Logging using Fabric does not consider any steps during training, unlike when using the Lightning Trainer. A LightningModule calling self.log simply passes the logged dictionary and nothing else to the Fabric logging code when using Fabric but when using the Trainer it is handled by grouping/frequency adjustments (such as aggregating during multi-gpu training or logging every X steps [default 50]).
Pitch
An option to enable similar logging in Fabric as the Lightning Trainer. This could be off by default but could track steps that are submitted with fabric hooks/calls, such as:
fabric.call('on_train_step')
This would allow for logged values to be aggregated during the same step, which makes logs more readable.
Description & Motivation
Logging using Fabric does not consider any steps during training, unlike when using the Lightning Trainer. A LightningModule calling self.log simply passes the logged dictionary and nothing else to the Fabric logging code when using Fabric but when using the Trainer it is handled by grouping/frequency adjustments (such as aggregating during multi-gpu training or logging every X steps [default 50]).
Pitch
An option to enable similar logging in Fabric as the Lightning Trainer. This could be off by default but could track steps that are submitted with fabric hooks/calls, such as:
fabric.call('on_train_step')
This would allow for logged values to be aggregated during the same step, which makes logs more readable.
Alternatives
No response
Additional context
No response
cc @Borda
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