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config activation
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@ -15,6 +15,7 @@ class SimpleAutoEncoder(AbstractModel):
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super().__init__(save_directory, model_name)
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self.activation = config['activation']
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self.input_shape = (config['input_height'], config['input_width'], config['input_channel'])
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self.lr = config['learning_rate']
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self.build_model()
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@ -39,7 +40,7 @@ class SimpleAutoEncoder(AbstractModel):
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# x = Conv2D(1, (3, 3), activation = 'relu', padding = 'same', name = 'dec_conv_1')(encoded)
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# x = UpSampling2D((2, 2))(x)
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# x = Flatten()(x)
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x = Dense(np.prod(input_shape), activation = 'softmax')(layer_5)
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x = Dense(np.prod(input_shape), activation = self.activation)(layer_5)
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decoded = Reshape((input_shape))(x)
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self.model = Model(picture, decoded)
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