remove lr_dropout for plaidml backend

This commit is contained in:
Colombo 2020-01-08 11:11:33 +04:00
parent d3e6b435aa
commit b8182ae42b
2 changed files with 9 additions and 5 deletions

View file

@ -141,8 +141,9 @@ class Quick96Model(ModelBase):
self.CA_conv_weights_list += [layer.weights[0]] #- is Conv2D kernel_weights
if self.is_training_mode:
self.src_dst_opt = RMSprop(lr=2e-4, lr_dropout=0.3)
self.src_dst_mask_opt = RMSprop(lr=2e-4, lr_dropout=0.3)
lr_dropout = 0.3 if nnlib.device.backend != 'plaidML' else 0.0
self.src_dst_opt = RMSprop(lr=2e-4, lr_dropout=lr_dropout)
self.src_dst_mask_opt = RMSprop(lr=2e-4, lr_dropout=lr_dropout)
target_src_masked = self.model.target_src*self.model.target_srcm
target_dst_masked = self.model.target_dst*self.model.target_dstm

View file

@ -65,9 +65,12 @@ class SAEHDModel(ModelBase):
default_bg_style_power = self.options.get('bg_style_power', 0.0)
if is_first_run or ask_override:
default_lr_dropout = self.options.get('lr_dropout', False)
self.options['lr_dropout'] = io.input_bool ( f"Use learning rate dropout? (y/n, ?:help skip:{yn_str[default_lr_dropout]} ) : ", default_lr_dropout, help_message="When the face is trained enough, you can enable this option to get extra sharpness for less amount of iterations.")
if nnlib.device.backend != 'plaidML':
default_lr_dropout = self.options.get('lr_dropout', False)
self.options['lr_dropout'] = io.input_bool ( f"Use learning rate dropout? (y/n, ?:help skip:{yn_str[default_lr_dropout]} ) : ", default_lr_dropout, help_message="When the face is trained enough, you can enable this option to get extra sharpness for less amount of iterations.")
else:
self.options['lr_dropout'] = False
default_random_warp = self.options.get('random_warp', True)
self.options['random_warp'] = io.input_bool (f"Enable random warp of samples? ( y/n, ?:help skip:{yn_str[default_random_warp]}) : ", default_random_warp, help_message="Random warp is required to generalize facial expressions of both faces. When the face is trained enough, you can disable it to get extra sharpness for less amount of iterations.")