h

app.py

@@ -18,7 +18,7 @@ from PIL import Image as im
 #openai.api_key  = os.getenv('OPENAI_API_KEY')
 
 class ContextUnet(nn.Module):
-    def __init__(self, in_channels, n_feat=256, n_cfeat=10, height=28):  # cfeat - context features
+    def __init__(self, in_channels, n_feat=256, n_cfeat=10, height=64):  # cfeat - context features
         super(ContextUnet, self).__init__()
 
         # number of input channels, number of intermediate feature maps and number of classes
@@ -106,7 +106,7 @@ beta2 = 0.02
 device = torch.device("cuda:0" if torch.cuda.is_available() else torch.device('cpu'))
 n_feat = 64 # 64 hidden dimension feature
 n_cfeat = 5 # context vector is of size 5
-height = 64 # 16x16 image
+height = 16 # 16x16 image
 save_dir = './weights/'
 
 # training hyperparameters