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ppocr/losses/rec_latexocr_loss.py

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+# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+This code is refer from:
+https://github.com/lucidrains/x-transformers/blob/main/x_transformers/autoregressive_wrapper.py
+"""
+
+import paddle
+import paddle.nn as nn
+import paddle.nn.functional as F
+import numpy as np
+
+
+class LaTeXOCRLoss(nn.Layer):
+    """
+    LaTeXOCR adopt CrossEntropyLoss for network training.
+    """
+
+    def __init__(self):
+        super(LaTeXOCRLoss, self).__init__()
+        self.ignore_index = -100
+        self.cross = nn.CrossEntropyLoss(
+            reduction="mean", ignore_index=self.ignore_index
+        )
+
+    def forward(self, preds, batch):
+        word_probs = preds
+        labels = batch[1][:, 1:]
+        word_loss = self.cross(
+            paddle.reshape(word_probs, [-1, word_probs.shape[-1]]),
+            paddle.reshape(labels, [-1]),
+        )
+
+        loss = word_loss
+        return {"loss": loss}