Fix tecogan_losses fp16

codes/models/steps/tecogan_losses.py

@@ -189,6 +189,8 @@ def create_teco_discriminator_sextuplet(input_list, lr_imgs, scale, index, flow_
 
 
 def create_all_discriminator_sextuplets(input_list, lr_imgs, scale, total, flow_gen, resampler, margin):
+    with autocast(enabled=False):
+        input_list = input_list.float()        
         # Combine everything and feed it into the flow network at once for better efficiency.
         batch_sz = input_list.shape[0]
         flux_doubles_forward = [torch.stack([input_list[:,i], input_list[:,i+1]], dim=2) for i in range(1, total+1)]