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Update Model.py

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SAEHD add lr_dropout,and modify learn rate to 1e-5
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cszdlt 2019-12-24 10:25:54 +08:00 • committed by GitHub
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1 changed files with 3 additions and 3 deletions
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models/Model_SAEHD/Model.py
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@ -452,9 +452,9 @@ class SAEHDModel(ModelBase):
psd_target_dst_anti_masked = self.model.pred_src_dst*(1.0 - target_dstm)
if self.is_training_mode:
self.src_dst_opt = RMSprop(lr=1e-6, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
self.src_dst_mask_opt = RMSprop(lr=1e-6, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
self.D_opt = RMSprop(lr=1e-6, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
self.src_dst_opt = RMSprop(lr=1e-5, lr_dropout=0.3, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
self.src_dst_mask_opt = RMSprop(lr=1e-5, lr_dropout=0.3, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
self.D_opt = RMSprop(lr=1e-5, lr_dropout=0.3, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1)
src_loss = K.mean ( 10*dssim(kernel_size=int(resolution/11.6),max_value=1.0)( target_src_masked_opt, pred_src_src_masked_opt) )
src_loss += K.mean ( 10*K.square( target_src_masked_opt - pred_src_src_masked_opt ) )