From 42a97de75697fd85a0bc8d26b405d1c98efa4ab1 Mon Sep 17 00:00:00 2001
From: James Betker <jbetker@gmail.com>
Date: Wed, 11 Nov 2020 12:14:14 -0700
Subject: [PATCH] Convert PyramidRRDBDisc to RRDBDisc
Had numeric stability issues. This probably makes more sense anyways.
---
codes/models/archs/discriminator_vgg_arch.py | 30 ++++++++++----------
codes/models/networks.py | 4 +--
2 files changed, 17 insertions(+), 17 deletions(-)
diff --git a/codes/models/archs/discriminator_vgg_arch.py b/codes/models/archs/discriminator_vgg_arch.py
index 2e26504e..6caeb05c 100644
--- a/codes/models/archs/discriminator_vgg_arch.py
+++ b/codes/models/archs/discriminator_vgg_arch.py
@@ -6,7 +6,7 @@ from models.archs.arch_util import ConvBnLelu, ConvGnLelu, ExpansionBlock, ConvG
import torch.nn.functional as F
from models.archs.SwitchedResidualGenerator_arch import gather_2d
from models.archs.pyramid_arch import Pyramid
-from utils.util import checkpoint
+from utils.util import checkpoint, sequential_checkpoint
class Discriminator_VGG_128(nn.Module):
@@ -662,24 +662,24 @@ class SingleImageQualityEstimator(nn.Module):
return fea
-class PyramidRRDBDiscriminator(nn.Module):
+class RRDBDiscriminator(nn.Module):
def __init__(self, in_nc, nf, block=ConvGnLelu):
- super(PyramidRRDBDiscriminator, self).__init__()
+ super(RRDBDiscriminator, self).__init__()
self.initial_conv = block(in_nc, nf, kernel_size=3, stride=2, bias=True, norm=False, activation=True)
- self.top_proc = nn.Sequential(*[RRDBWithBypass(nf),
- RRDBWithBypass(nf)])
- self.pyramid = Pyramid(nf, depth=3, processing_convs_per_layer=2, processing_at_point=2,
- scale_per_level=1.5, norm=True, return_outlevels=False)
- self.bottom_proc = nn.Sequential(*[RRDBWithBypass(nf),
- RRDBWithBypass(nf),
- ConvGnLelu(nf, nf // 2, kernel_size=1, activation=True, norm=True, bias=True),
- ConvGnLelu(nf // 2, nf // 4, kernel_size=1, activation=True, norm=True, bias=True),
- ConvGnLelu(nf // 4, 1, activation=False, norm=False, bias=True)])
+ self.trunk = nn.ModuleList(*[RRDBWithBypass(nf),
+ RRDBWithBypass(nf),
+ RRDBWithBypass(nf),
+ RRDBWithBypass(nf),
+ RRDBWithBypass(nf)])
+
+ self.tail = nn.Sequential(*[
+ ConvGnLelu(nf, nf // 2, kernel_size=1, activation=True, norm=True, bias=True),
+ ConvGnLelu(nf // 2, nf // 4, kernel_size=1, activation=True, norm=True, bias=True),
+ ConvGnLelu(nf // 4, 1, activation=False, norm=False, bias=True)])
def forward(self, x):
fea = self.initial_conv(x)
- fea = checkpoint(self.top_proc, fea)
- fea = checkpoint(self.pyramid, fea)
- fea = checkpoint(self.bottom_proc, fea)
+ fea = sequential_checkpoint(self.top_proc, 2, fea)
+ fea = checkpoint(self.tail, fea)
return torch.mean(fea, dim=[1,2,3])
diff --git a/codes/models/networks.py b/codes/models/networks.py
index dfc01983..2a67904e 100644
--- a/codes/models/networks.py
+++ b/codes/models/networks.py
@@ -187,8 +187,8 @@ def define_D_net(opt_net, img_sz=None, wrap=False):
netD = SRGAN_arch.RefDiscriminatorVgg128(in_nc=opt_net['in_nc'], nf=opt_net['nf'], input_img_factor=img_sz / 128)
elif which_model == "psnr_approximator":
netD = SRGAN_arch.PsnrApproximator(nf=opt_net['nf'], input_img_factor=img_sz / 128)
- elif which_model == "pyramid_rrdb_disc":
- netD = SRGAN_arch.PyramidRRDBDiscriminator(in_nc=3, nf=opt_net['nf'])
+ elif which_model == "rrdb_disc":
+ netD = SRGAN_arch.RRDBDiscriminator(in_nc=3, nf=opt_net['nf'])
else:
raise NotImplementedError('Discriminator model [{:s}] not recognized'.format(which_model))
return netD