update basecode_layer

config/config.yaml

@@ -20,6 +20,7 @@ paths:
 
 prompt: red lipstick
 resolution: 1024
+basecode_spatial_size: 16
 # available attributes
 # ['Blond_Hair', 'Wavy_Hair', 'Young', 'Eyeglasses', 'Heavy_Makeup', 'Rosy_Cheeks',
 #                               'Chubby', 'Mouth_Slightly_Open', 'Bushy_Eyebrows', 'Wearing_Lipstick', 'Smiling',

model.py

@@ -13,7 +13,7 @@ import hydra
 from omegaconf import DictConfig, OmegaConf
 import sys
 import os
-sys.path.append('./pixel2style2pixel')
+import numpy as np
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
@@ -72,6 +72,8 @@ class GanAttack(nn.Module):
                                  nn.ReLU(inplace=True),
                                  nn.Linear(4096, 512)
         )
+        basecode_layer = int(np.log2(cfg.basecode_spatial_size) - 2) * 2
+        self.basecode_layer=basecode_layer = f'x{basecode_layer-1:02d}'
         
 
 
@@ -82,7 +84,8 @@ class GanAttack(nn.Module):
         x_prompt=torch.cat([basecode,prompt],dim=2)
         x_prompt=self.mlp(x_prompt)
         x=x_prompt+x
-        result_images=self.generator.synthesis(detailcode,randomize_noise=False,basecode=x)['image']
+        result_images=self.generator.synthesis(detailcode,randomize_noise=False,
+                                               basecode_layer=self.basecode_layer,basecode=x)['image']
         
 
         return result_images,x