diff --git a/codes/models/archs/SwitchedResidualGenerator_arch.py b/codes/models/archs/SwitchedResidualGenerator_arch.py
index 6214aa5b..38d3846a 100644
--- a/codes/models/archs/SwitchedResidualGenerator_arch.py
+++ b/codes/models/archs/SwitchedResidualGenerator_arch.py
@@ -316,7 +316,8 @@ class ConfigurableSwitchedResidualGenerator2(nn.Module):
         switches = []
         post_switch_proc = []
         self.initial_conv = ConvBnLelu(3, transformation_filters, bn=False)
-        self.final_conv = ConvBnLelu(transformation_filters, 3, bn=False)
+        self.proc_conv = ConvBnLelu(transformation_filters, transformation_filters, bn=False)
+        self.final_conv = ConvBnLelu(transformation_filters, 3, bn=False, lelu=False)
         for filters, growth, sw_reduce, sw_proc, trans_count, kernel, layers in zip(switch_filters, switch_growths, switch_reductions, switch_processing_layers, trans_counts, trans_kernel_sizes, trans_layers):
             multiplx_fn = functools.partial(ConvBasisMultiplexer, transformation_filters, filters, growth, sw_reduce, sw_proc, trans_count)
             switches.append(ConfigurableSwitchComputer(multiplx_fn, functools.partial(MultiConvBlock, transformation_filters, transformation_filters, transformation_filters, kernel_size=kernel, depth=layers), trans_count, initial_temp, enable_negative_transforms=enable_negative_transforms, add_scalable_noise_to_transforms=add_scalable_noise_to_transforms))
@@ -346,6 +347,12 @@ class ConfigurableSwitchedResidualGenerator2(nn.Module):
             x = x + sw_out
             x = x + conv(x)
 
+        # This network is entirely a "repair" network and operates on full-resolution images. Upsample first if that
+        # is called for, then repair.
+        if self.upsample_factor > 1:
+            x = F.interpolate(x, scale_factor=self.upsample_factor, mode="nearest")
+
+        x = self.proc_conv(x)
         x = self.final_conv(x)
         return x,