zero init final projection in unet, since openai and @crowsonkb are both doing it

dalle2_pytorch/dalle2_pytorch.py

@@ -77,6 +77,11 @@ def cast_tuple(val, length = None):
 def module_device(module):
     return next(module.parameters()).device
 
+def zero_init_(m):
+    nn.init.zeros_(m.weight)
+    if exists(m.bias):
+        nn.init.zeros_(m.bias)
+
 @contextmanager
 def null_context(*args, **kwargs):
     yield
@@ -1669,6 +1674,8 @@ class Unet(nn.Module):
         self.final_resnet_block = ResnetBlock(dim * 2, dim, time_cond_dim = time_cond_dim, groups = top_level_resnet_group)
         self.to_out = nn.Conv2d(dim, self.channels_out, kernel_size = final_conv_kernel_size, padding = final_conv_kernel_size // 2)
 
+        zero_init_(self.to_out) # since both OpenAI and @crowsonkb are doing it
+
     # if the current settings for the unet are not correct
     # for cascading DDPM, then reinit the unet with the right settings
     def cast_model_parameters(

dalle2_pytorch/version.py

@@ -1 +1 @@
-__version__ = '0.20.0'
+__version__ = '0.20.1'