fixed config

src/aiunn/config.py

@@ -1,27 +1,40 @@
 from aiia import AIIAConfig
-import os
-import json
 
 
 class UpsamplerConfig(AIIAConfig):
     def __init__(
         self,
+        base_config=None,
         upsample_scale: int = 2,
         upsample_mode: str = 'bilinear',
         upsample_align_corners: bool = False,
         layers=None,
         **kwargs
     ):
-        # Initialize base configuration.
-        super().__init__(**kwargs)
-        self.layers = layers if layers is not None else []
+        # Start with a single configuration dictionary.
+        config_data = {}
+        if base_config is not None:
+            # If base_config is an object with a to_dict method, use it.
+            if hasattr(base_config, "to_dict"):
+                config_data.update(base_config.to_dict())
+            elif isinstance(base_config, dict):
+                config_data.update(base_config)
+        
+        # Update with any additional keyword arguments (if needed).
+        config_data.update(kwargs)
+        
+        # Initialize base AIIAConfig with a single merged configuration.
+        super().__init__(**config_data)
         
         # Upsampler-specific parameters.
         self.upsample_scale = upsample_scale
         self.upsample_mode = upsample_mode
         self.upsample_align_corners = upsample_align_corners
         
-        # Automatically add the upsample layer details.
+        # Use layers from the argument or initialize an empty list.
+        self.layers = layers if layers is not None else []
+        
+        # Add the upsample layer details only once.
         self.add_upsample_layer()
 
     def add_upsample_layer(self):
@@ -32,6 +45,6 @@ class UpsamplerConfig(AIIAConfig):
             'mode': self.upsample_mode,
             'align_corners': self.upsample_align_corners
         }
-        # Add the upsample layer only if not already present.
+        # Append the layer only if it isn’t already present.
         if not any(layer.get('name') == 'Upsample' for layer in self.layers):
             self.layers.append(upsample_layer)

src/aiunn/upsampler.py

@@ -11,7 +11,10 @@ class Upsampler(AIIA):
     def __init__(self, base_model: AIIABase):
         super().__init__(base_model.config)
         self.base_model = base_model
-        self.config = UpsamplerConfig(kwargs=self.base_model.config)
+        
+        # Pass the unified base configuration using the new parameter.
+        self.config = UpsamplerConfig(base_config=base_model.config)
+        
         self.upsample = nn.Upsample(
             scale_factor=self.config.upsample_scale,
             mode=self.config.upsample_mode,
@@ -24,6 +27,7 @@ class Upsampler(AIIA):
             kernel_size=1
         )
 
+
     def forward(self, x):
         x = self.base_model(x)
         x = self.upsample(x)