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modeling_solider.py

@@ -27,6 +27,8 @@ from itertools import repeat
 import collections.abc
 
 from .configuration_solider import SOLIDERConfig, BACKBONE_NAME2WIDTH
+
+
 def _ntuple(n):
     def parse(x):
         if isinstance(x, collections.abc.Iterable):
@@ -1628,7 +1630,6 @@ def build_solider(cfg: dict) -> SwinTransformer:
 # }
 
 
-
 SOLIDER_BASE_MODEL_CONFIG_PARAMETERS = {
     "pretrain_img_size": [224, 224],
     "in_channels": 3,
@@ -1771,14 +1772,12 @@ class SOLIDERModel(PreTrainedModel):
         self.solider_name = config.name
         self.vision_width = BACKBONE_NAME2WIDTH[self.solider_name]
         self.hidden_size = self.vision_width
-        
+
         self.config = config
         # self.init_weights()
 
-    def forward(self, x, semantic_weight=None):
-        if semantic_weight is None:
-            semantic_weight = self.config.semantic_weight
-        return self.solider(x, semantic_weight)
+    def forward(self, x):
+        return self.solider(x, None)
 
 
 # NOTE: Currently not used!
@@ -1791,7 +1790,7 @@ class SoliderEncoder(SwinTransformer):
 
     @classmethod
     def from_config(cls, cfg, from_pretrained=None):
-        
+
         name = cfg.get("name", "swin_small_patch4_window7_224")
         img_size = cfg.get("img_size", [384, 128])
         drop_path_rate = cfg.get("drop_path_rate", 0.1)
@@ -1840,8 +1839,5 @@ class SoliderEncoder(SwinTransformer):
         model.config = cfg
         return model
 
-    def forward_features(self, x, semantic_weight=None):
-        if semantic_weight is None:
-            semantic_weight = self.config.semantic_weight
-        return SwinTransformer.forward(self, x, semantic_weight)
-    
+    def forward_features(self, x):
+        return SwinTransformer.forward(self, x, None)