From b62eb0da38a273b2b664ecf82626d69784fd78de Mon Sep 17 00:00:00 2001 From: cszdlt Date: Mon, 2 Dec 2019 23:39:03 +0800 Subject: [PATCH 1/4] modify learn rate to 1e-5 --- models/Model_SAEHD/Model.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py index 1ee851f..0d5dac3 100644 --- a/models/Model_SAEHD/Model.py +++ b/models/Model_SAEHD/Model.py @@ -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=5e-5, 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=5e-5, clipnorm=1.0 if self.options['clipgrad'] else 0.0, tf_cpu_mode=self.options['optimizer_mode']-1) - self.D_opt = RMSprop(lr=5e-5, 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, 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, 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, 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 ) ) From 30ef74cad316596c0737644694df67bd16106ec0 Mon Sep 17 00:00:00 2001 From: cszdlt <1106543196@qq.com> Date: Tue, 3 Dec 2019 15:21:55 +0800 Subject: [PATCH 2/4] Update Model.py modify learn rate to 1e-6 --- models/Model_SAEHD/Model.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py index 0d5dac3..0e35073 100644 --- a/models/Model_SAEHD/Model.py +++ b/models/Model_SAEHD/Model.py @@ -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-5, 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, 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, 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-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) 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 ) ) From fe724c8322c778e162321e4e56641bf972c9983d Mon Sep 17 00:00:00 2001 From: cszdlt <1106543196@qq.com> Date: Tue, 24 Dec 2019 10:25:54 +0800 Subject: [PATCH 3/4] Update Model.py SAEHD add lr_dropout,and modify learn rate to 1e-5 --- models/Model_SAEHD/Model.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py index 0e35073..76c35ec 100644 --- a/models/Model_SAEHD/Model.py +++ b/models/Model_SAEHD/Model.py @@ -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 ) ) From 28549dc153948f3dd91bddfdc57ea9cc7cb87d66 Mon Sep 17 00:00:00 2001 From: Colombo Date: Sat, 28 Dec 2019 16:50:33 +0400 Subject: [PATCH 4/4] SAEHD:optimized architecture, you have to restart training --- models/Model_SAEHD/Model.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py index b02f2de..cc9217c 100644 --- a/models/Model_SAEHD/Model.py +++ b/models/Model_SAEHD/Model.py @@ -198,8 +198,6 @@ class SAEHDModel(ModelBase): if dims % 2 != 0: dims += 1 - - def func(x): for i in [8,4,2]: @@ -213,7 +211,7 @@ class SAEHDModel(ModelBase): x = Add()([x, x0]) x = LeakyReLU(0.2)(x) - return Conv2D(output_nc, kernel_size=5, padding='same', activation='sigmoid')(x) + return Conv2D(output_nc, kernel_size=1, padding='same', activation='sigmoid')(x) return func @@ -327,7 +325,7 @@ class SAEHDModel(ModelBase): x = Add()([x, x0]) x = LeakyReLU(0.2)(x) - return Conv2D(output_nc, kernel_size=5, padding='same', activation='sigmoid')(x) + return Conv2D(output_nc, kernel_size=1, padding='same', activation='sigmoid')(x) return func