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@aniketmaurya
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PL LightningModule automatically sets train and eval mode and torch.no_grad during the training and validation steps.

self.accumulate_metrics(preds=preds)
self.train()
train_preds = self(xb, yb)
loss = loss_fn(train_preds, yb)
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I wasn't able to understand why do we calculate training prediction here?

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Maybe the name is misleading , these are in fact validation preds. These are used to calculate validation loss and metrics

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codecov bot commented May 16, 2022

Codecov Report

Merging #1100 (13bb3e7) into master (743cb7d) will increase coverage by 0.00%.
The diff coverage is 80.00%.

@@           Coverage Diff           @@
##           master    #1100   +/-   ##
=======================================
  Coverage   85.43%   85.44%           
=======================================
  Files         301      301           
  Lines        6600     6594    -6     
=======================================
- Hits         5639     5634    -5     
+ Misses        961      960    -1     
Flag Coverage Δ
unittests 85.44% <80.00%> (+<0.01%) ⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
...odels/ross/efficientdet/lightning/model_adapter.py 37.93% <0.00%> (+1.26%) ⬆️
icevision/models/mmdet/lightning/model_adapter.py 96.96% <100.00%> (-0.26%) ⬇️
...sion/models/torchvision/lightning_model_adapter.py 100.00% <100.00%> (ø)
...dels/ultralytics/yolov5/lightning/model_adapter.py 100.00% <100.00%> (ø)

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@potipot
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potipot commented May 17, 2022

Any idea why black formatting check might failing here?

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2 participants