Remove criterion and ctc loss

2 files changed, 0 insertions, 39 deletions

diff --git a/text_recognizer/criterion/__init__.py b/text_recognizer/criterion/__init__.py
deleted file mode 100644
index 5b0a7ab..0000000
--- a/text_recognizer/criterion/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-"""Module with custom loss functions."""
diff --git a/text_recognizer/criterion/ctc.py b/text_recognizer/criterion/ctc.py
deleted file mode 100644
index 42a0b25..0000000
--- a/text_recognizer/criterion/ctc.py
+++ /dev/null
@@ -1,38 +0,0 @@
-"""CTC loss."""
-import torch
-from torch import LongTensor, nn, Tensor
-import torch.nn.functional as F
-
-
-class CTCLoss(nn.Module):
-    """CTC loss."""
-
-    def __init__(self, blank: int) -> None:
-        super().__init__()
-        self.blank = blank
-
-    def forward(self, outputs: Tensor, targets: Tensor) -> Tensor:
-        """Computes the CTC loss."""
-        device = outputs.device
-
-        log_probs = F.log_softmax(outputs, dim=2).permute(1, 0, 2)
-        output_lengths = LongTensor([outputs.shape[1]] * outputs.shape[0]).to(device)
-
-        targets_ = LongTensor([]).to(device)
-        target_lengths = LongTensor([]).to(device)
-        for target in targets:
-            # Remove padding
-            target = target[target != self.blank].to(device)
-            targets_ = torch.cat((targets_, target))
-            target_lengths = torch.cat(
-                (target_lengths, torch.LongTensor([len(target)]).to(device)), dim=0
-            )
-
-        return F.ctc_loss(
-            log_probs,
-            targets,
-            output_lengths,
-            target_lengths,
-            blank=self.blank,
-            zero_infinity=True,
-        )