Anpassungen an der modeling

segformer_plusplus/modeling_segformer_plusplus.py

@@ -1,13 +1,6 @@
-# modeling_segformer_plusplus.py
-
 from typing import Optional, Tuple
-import torch
 import torch.nn as nn
 from transformers import PreTrainedModel, PretrainedConfig
-from transformers.modeling_outputs import SemanticSegmenterOutput
-
-# Falls du SegFormer direkt importieren willst, musst du sicherstellen,
-# dass diese Klasse im selben Repo verfügbar ist.
 from segformer_plusplus.model import create_model
 
 
@@ -47,23 +40,5 @@ class SegformerPlusPlusForSemanticSegmentation(PreTrainedModel):
             backbone=config.backbone,
             tome_strategy=config.tome_strategy,
             out_channels=config.num_labels,
-            pretrained=False,  # Kein Pretrained hier – wird über .from_pretrained geladen
-        )
-
-    def forward(
-        self,
-        pixel_values: torch.FloatTensor,
-        labels: Optional[torch.LongTensor] = None,
-    ) -> SemanticSegmenterOutput:
-
-        logits = self.segformer(pixel_values)
-
-        loss = None
-        if labels is not None:
-            loss_fct = nn.CrossEntropyLoss(ignore_index=255)
-            loss = loss_fct(logits, labels.long())
-
-        return SemanticSegmenterOutput(
-            loss=loss,
-            logits=logits,
+            pretrained=False,
         )