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iperov 2019-04-19 20:22:21 +04:00
commit e980a5fffd
1 changed files with 3 additions and 4 deletions
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7
models/Model_RecycleGAN/Model.py
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@ -48,8 +48,8 @@ class RecycleGANModel(ModelBase):
self.PA = modelify(RecycleGANModel.UNetTemporalPredictor(bgr_shape[2], use_batch_norm, ngf=npf))([Input(bgr_shape), Input(bgr_shape)])
self.PB = modelify(RecycleGANModel.UNetTemporalPredictor(bgr_shape[2], use_batch_norm, ngf=npf))([Input(bgr_shape), Input(bgr_shape)])
self.DA = modelify(RecycleGANModel.NLayerDiscriminator(ndf=ndf) ) (Input(bgr_shape))
self.DB = modelify(RecycleGANModel.NLayerDiscriminator(ndf=ndf) ) (Input(bgr_shape))
self.DA = modelify(RecycleGANModel.PatchDiscriminator(ndf=ndf) ) (Input(bgr_shape))
self.DB = modelify(RecycleGANModel.PatchDiscriminator(ndf=ndf) ) (Input(bgr_shape))
if not self.is_first_run():
weights_to_load = [
@ -292,7 +292,7 @@ class RecycleGANModel(ModelBase):
x = input
x = XConv2D(ngf, 7, strides=1, use_bias=True)(x)
x = ReLU()(XNormalization(XConv2D(ngf, 7, strides=1)(x)))
x = ReLU()(XNormalization(XConv2D(ngf*2, 3, strides=2)(x)))
x = ReLU()(XNormalization(XConv2D(ngf*4, 3, strides=2)(x)))
@ -463,7 +463,6 @@ class RecycleGANModel(ModelBase):
x = XConv2D( f, 4, strides=2, padding='valid')(x)
f = min( ndf*8, f*2 )
x = XNormalization(x)
x = Dropout(0.5)(x)
x = LeakyReLU(0.2)(x)
x = ZeroPadding2D((1,1))(x)