def eval_initialize(self, opt):
BaseModel.eval_initialize(self, opt)
args = {'scale': opt.sr_factor, 'n_feats': 256, 'n_resblocks': 32, 'res_scale': 0.1, 'n_colors': 3,
'rgb_range': opt.rgb_range}
self.model = EDSR(args).to(self.device)
self.model = nn.DataParallel(self.model, opt.gpu_ids)
def eval_initialize(self, opt):
BaseModel.eval_initialize(self, opt)
args = {'scale': opt.sr_factor, 'n_resgroups': 10, 'n_feats': 64, 'n_resblocks': 20, 'res_scale': 1,
'n_colors': 3,
'reduction': 16, 'rgb_range': opt.rgb_range}
self.model = RCAN(args).to(self.device)
self.model = nn.DataParallel(self.model, opt.gpu_ids)
def eval_initialize(self, opt):
BaseModel.eval_initialize(self, opt)
kernel_size = 3
n_colors = opt.n_colors
self.model = NonLocalModule(kernel_size, n_colors, self.device)
self.model = nn.DataParallel(self.model, opt.gpu_ids)
self.model.to(self.device)
def eval_initialize(self, opt):
BaseModel.eval_initialize(self, opt)
args = {
'scale': opt.sr_factor,
'G0': 64,
'RDNkSize': 3,
'RDNconfig': 'B',
'n_colors': 3
}
self.model = RDN(args).to(self.device)
self.model = nn.DataParallel(self.model, opt.gpu_ids)
def eval_initialize(self, opt):
BaseModel.eval_initialize(self, opt)
SR_args = {
'scale': opt.sr_factor,
'n_feats': opt.n_feats,
'n_resblocks': opt.n_resblocks,
'n_colors': opt.n_colors,
'main_model': opt.main_model,
'recur_step': opt.recur_step,
'res_scale': opt.res_scale,
'device': self.device,
'n_resgroups1': opt.n_resgroups1,
'n_resgroups2': opt.n_resgroups2,
'rgb_range': opt.rgb_range
}
self.sr_factor = opt.sr_factor
self.model = PSIARRENet(SR_args)
self.model = nn.DataParallel(self.model, device_ids=opt.gpu_ids)
self.model.to(self.device)
if opt.n_resgroups1 == 2:
self.tiny = True
else:
self.tiny = False
