@@ -175,6 +175,7 @@ def forward(self, x):
175175
176176
177177# unet.py, unet_grad_tts.py, unet_ldm.py, unet_glide.py, unet_score_vde.py
178+ # => All 2D-Resnets are included here now!
178179class ResnetBlock (nn .Module ):
179180 def __init__ (
180181 self ,
@@ -317,9 +318,6 @@ def __init__(
317318 num_groups = min (in_ch // 4 , 32 )
318319 num_groups_out = min (out_ch // 4 , 32 )
319320 temb_dim = temb_channels
320- # output_scale_factor = np.sqrt(2.0)
321- # non_linearity = "silu"
322- # use_nin_shortcut = in_channels != out_channels or use_nin_shortcut = True
323321
324322 self .GroupNorm_0 = nn .GroupNorm (num_groups = num_groups , num_channels = in_ch , eps = eps )
325323 self .up = up
@@ -337,13 +335,9 @@ def __init__(
337335 # 1x1 convolution with DDPM initialization.
338336 self .Conv_2 = conv2d (in_ch , out_ch , kernel_size = 1 , padding = 0 )
339337
340- # self.skip_rescale = skip_rescale
341338 self .in_ch = in_ch
342339 self .out_ch = out_ch
343340
344- # TODO(Patrick) - move to main init
345- self .is_overwritten = False
346-
347341 def set_weights_grad_tts (self ):
348342 self .conv1 .weight .data = self .block1 .block [0 ].weight .data
349343 self .conv1 .bias .data = self .block1 .block [0 ].bias .data
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