directly convert list to tensor

modules/sd_hijack.py

@@ -232,10 +232,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         z = outputs.last_hidden_state
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
-        if torch.has_mps:
-            batch_multipliers = torch.asarray(np.array(batch_multipliers).astype('float32')).to(device)
-        else:
-            batch_multipliers = torch.asarray(np.array(batch_multipliers)).to(device)
+        batch_multipliers = torch.asarray(batch_multipliers).to(device)
         original_mean = z.mean()
         z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
         new_mean = z.mean()