Convert PyramidRRDBDisc to RRDBDisc
Had numeric stability issues. This probably makes more sense anyways.
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@ -6,7 +6,7 @@ from models.archs.arch_util import ConvBnLelu, ConvGnLelu, ExpansionBlock, ConvG
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import torch.nn.functional as F
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from models.archs.SwitchedResidualGenerator_arch import gather_2d
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from models.archs.pyramid_arch import Pyramid
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from utils.util import checkpoint
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from utils.util import checkpoint, sequential_checkpoint
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class Discriminator_VGG_128(nn.Module):
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@ -662,24 +662,24 @@ class SingleImageQualityEstimator(nn.Module):
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return fea
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class PyramidRRDBDiscriminator(nn.Module):
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class RRDBDiscriminator(nn.Module):
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def __init__(self, in_nc, nf, block=ConvGnLelu):
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super(PyramidRRDBDiscriminator, self).__init__()
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super(RRDBDiscriminator, self).__init__()
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self.initial_conv = block(in_nc, nf, kernel_size=3, stride=2, bias=True, norm=False, activation=True)
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self.top_proc = nn.Sequential(*[RRDBWithBypass(nf),
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RRDBWithBypass(nf)])
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self.pyramid = Pyramid(nf, depth=3, processing_convs_per_layer=2, processing_at_point=2,
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scale_per_level=1.5, norm=True, return_outlevels=False)
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self.bottom_proc = nn.Sequential(*[RRDBWithBypass(nf),
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self.trunk = nn.ModuleList(*[RRDBWithBypass(nf),
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RRDBWithBypass(nf),
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RRDBWithBypass(nf),
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RRDBWithBypass(nf),
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RRDBWithBypass(nf)])
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self.tail = nn.Sequential(*[
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ConvGnLelu(nf, nf // 2, kernel_size=1, activation=True, norm=True, bias=True),
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ConvGnLelu(nf // 2, nf // 4, kernel_size=1, activation=True, norm=True, bias=True),
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ConvGnLelu(nf // 4, 1, activation=False, norm=False, bias=True)])
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def forward(self, x):
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fea = self.initial_conv(x)
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fea = checkpoint(self.top_proc, fea)
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fea = checkpoint(self.pyramid, fea)
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fea = checkpoint(self.bottom_proc, fea)
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fea = sequential_checkpoint(self.top_proc, 2, fea)
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fea = checkpoint(self.tail, fea)
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return torch.mean(fea, dim=[1,2,3])
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@ -187,8 +187,8 @@ def define_D_net(opt_net, img_sz=None, wrap=False):
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netD = SRGAN_arch.RefDiscriminatorVgg128(in_nc=opt_net['in_nc'], nf=opt_net['nf'], input_img_factor=img_sz / 128)
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elif which_model == "psnr_approximator":
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netD = SRGAN_arch.PsnrApproximator(nf=opt_net['nf'], input_img_factor=img_sz / 128)
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elif which_model == "pyramid_rrdb_disc":
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netD = SRGAN_arch.PyramidRRDBDiscriminator(in_nc=3, nf=opt_net['nf'])
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elif which_model == "rrdb_disc":
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netD = SRGAN_arch.RRDBDiscriminator(in_nc=3, nf=opt_net['nf'])
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else:
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raise NotImplementedError('Discriminator model [{:s}] not recognized'.format(which_model))
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return netD
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