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Invert ResGen2 to operate in LR space

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This commit is contained in:
James Betker 2020-06-30 20:57:40 -06:00
parent e07d8abafb
commit 87f1e9c56f
1 changed files with 8 additions and 1 deletions
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9
codes/models/archs/SwitchedResidualGenerator_arch.py
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@ -316,7 +316,8 @@ class ConfigurableSwitchedResidualGenerator2(nn.Module):
switches = [] switches = []
post_switch_proc = [] post_switch_proc = []
self.initial_conv = ConvBnLelu(3, transformation_filters, bn=False) 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): 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) 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)) 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 + sw_out
x = x + conv(x) 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) x = self.final_conv(x)
return x, return x,