From 0a714e8451e1c168b689ade39eb11fe9d59747a2 Mon Sep 17 00:00:00 2001
From: James Betker <jbetker@gmail.com>
Date: Mon, 15 Jun 2020 21:32:03 -0600
Subject: [PATCH] Fix initialization in mhead switched rrdb
---
codes/models/archs/RRDBNet_arch.py | 1 +
codes/models/archs/arch_util.py | 2 +-
codes/models/networks.py | 9 +--------
3 files changed, 3 insertions(+), 9 deletions(-)
diff --git a/codes/models/archs/RRDBNet_arch.py b/codes/models/archs/RRDBNet_arch.py
index fc7725ce..af0139ac 100644
--- a/codes/models/archs/RRDBNet_arch.py
+++ b/codes/models/archs/RRDBNet_arch.py
@@ -85,6 +85,7 @@ class ResidualDenseBlock_5C_WithMheadConverter(ResidualDenseBlock_5C):
late_stage_padding=0)
self.heads = heads
self.converter = nn.Conv3d(nf, nf, kernel_size=(heads, 1, 1), stride=(heads, 1, 1))
+ arch_util.initialize_weights(self.converter)
# Accepts input of shape (b, heads, f, w, h)
def forward(self, x):
diff --git a/codes/models/archs/arch_util.py b/codes/models/archs/arch_util.py
index ecb7be76..f79d4532 100644
--- a/codes/models/archs/arch_util.py
+++ b/codes/models/archs/arch_util.py
@@ -13,7 +13,7 @@ def initialize_weights(net_l, scale=1):
net_l = [net_l]
for net in net_l:
for m in net.modules():
- if isinstance(m, nn.Conv2d):
+ if isinstance(m, nn.Conv2d) or isinstance(m, nn.Conv3d):
init.kaiming_normal_(m.weight, a=0, mode='fan_in')
m.weight.data *= scale # for residual block
if m.bias is not None:
diff --git a/codes/models/networks.py b/codes/models/networks.py
index cc1fb6e0..1da351dc 100644
--- a/codes/models/networks.py
+++ b/codes/models/networks.py
@@ -80,14 +80,7 @@ def define_G(opt, net_key='network_G'):
'''netG = FlatProcessorNet_arch.FlatProcessorNet(in_nc=opt_net['in_nc'], out_nc=opt_net['out_nc'],
nf=opt_net['nf'], downscale=opt_net['scale'], reduce_anneal_blocks=opt_net['ra_blocks'],
assembler_blocks=opt_net['assembler_blocks'])'''
- netG = FlatProcessorNetNew_arch.fixup_resnet34(num_filters=opt_net['nf'])
- # video restoration
- elif which_model == 'EDVR':
- netG = EDVR_arch.EDVR(nf=opt_net['nf'], nframes=opt_net['nframes'],
- groups=opt_net['groups'], front_RBs=opt_net['front_RBs'],
- back_RBs=opt_net['back_RBs'], center=opt_net['center'],
- predeblur=opt_net['predeblur'], HR_in=opt_net['HR_in'],
- w_TSA=opt_net['w_TSA'])
+ netG = FlatProcessorNetNew_arch.fixup_resnet34(num_filters=opt_net['nf'])\
else:
raise NotImplementedError('Generator model [{:s}] not recognized'.format(which_model))