ref: decoupled ddp spawn (#3746)
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@ -393,7 +393,7 @@ If you want to calculate epoch-level metrics and log them, use the `.log` method
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loss = F.cross_entropy(y_hat, y)
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# logs metrics for each training_step, and the average across the epoch, to the progress bar and logger
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result.log('train_loss', loss, on_step=True, on_epoch=True, prog_bar=True, logger=True)
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self.log('train_loss', loss, on_step=True, on_epoch=True, prog_bar=True, logger=True)
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return loss
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The `.log` object automatically reduces the requested metrics across the full epoch.
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