sequential instead of loopback

model.py

@@ -3,7 +3,7 @@ import torch
 import torch.nn as nn
 from torch.optim.lr_scheduler import ReduceLROnPlateau
 
-from losses import circle_norm, preservation_loss
+from losses import circle_norm, preservation_loss  # noqa: F401
 from utils import RGBMYC_ANCHOR
 
 
@@ -28,7 +28,10 @@ class ColorTransformerModel(L.LightningModule):
         w = self.hparams.width
         d = self.hparams.depth
         bias = self.hparams.bias
-        midlayers = [nn.Linear(w, w, bias=bias), t()] * d
+        midlayers = []
+        for _ in range(d):
+            midlayers += [nn.Linear(w, w, bias=bias), t()]
+
         self.network = nn.Sequential(
             nn.Linear(3, w, bias=bias),
             t(),

newmain.py

@@ -13,16 +13,3 @@ def cli_main():
 if __name__ == "__main__":
     cli_main()
     # note: it is good practice to implement the CLI in a function and call it in the main if block
-
-
-# save_img_callback = SaveImageCallback(
-#     save_interval=0,
-#     final_dir="out",
-# )
-
-# trainer = pl.Trainer(
-#     callbacks=[save_img_callback],
-# )
-
-# data = ColorDataModule()
-# trainer.fit(model, data)

out/index.html

@@ -72,7 +72,7 @@
         function loadImages() {
             var gallery = document.getElementById('gallery');
 
-            for (var i = 0; i < 100; i++) { // Changed from i <= 100 to i < 100
+            for (var i = 0; i < 200; i++) { // Changed from i <= 100 to i < 100
                 let imageName;
                 if (i == -21) {
                     imageName = 'hsv.png';