From d386af7d32bfb37f53bc7292710ae1637e6cb1a9 Mon Sep 17 00:00:00 2001 From: macimovic Date: Fri, 27 Sep 2024 11:41:34 +0200 Subject: [PATCH] ignoring mypy complaints as the code that it complains about will never get executed when model is none for orientation classification --- doctr/models/classification/predictor/pytorch.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doctr/models/classification/predictor/pytorch.py b/doctr/models/classification/predictor/pytorch.py index 6d38e7bf1..96f5c468f 100644 --- a/doctr/models/classification/predictor/pytorch.py +++ b/doctr/models/classification/predictor/pytorch.py @@ -52,7 +52,7 @@ def forward( self.model, processed_batches = set_device_and_dtype( self.model, processed_batches, _params.device, _params.dtype ) - predicted_batches = [self.model(batch) for batch in processed_batches if self.model is not None] + predicted_batches = [self.model(batch) for batch in processed_batches] # type: ignore[misc] # confidence probs = [ torch.max(torch.softmax(batch, dim=1), dim=1).values.cpu().detach().numpy() for batch in predicted_batches @@ -61,7 +61,7 @@ def forward( predicted_batches = [out_batch.argmax(dim=1).cpu().detach().numpy() for out_batch in predicted_batches] class_idxs = [int(pred) for batch in predicted_batches for pred in batch] - classes = [int(self.model.cfg["classes"][idx]) for idx in class_idxs if self.model is not None] + classes = [int(self.model.cfg["classes"][idx]) for idx in class_idxs] # type: ignore[union-attr] confs = [round(float(p), 2) for prob in probs for p in prob] return [class_idxs, classes, confs]