zoo/inception/inception_v1_c.py
def classifier(self, x, n_classes, dropout=0.4):
        """ Construct the Classifier Group 
            x         : input to the classifier
            n_classes : number of output classes
            dropout   : percentage for dropout rate
        """
        # Save the encoding layer
        self.encoding = x
        
        # Pool at the end of all the convolutional residual blocks
        x = AveragePooling2D((7, 7))(x)
        x = Flatten()(x)

        # Save the embedding layer
        self.embedding = x

        outputs = super().classifier(x, n_classes, pooling=None, dropout=dropout)
        return outputs
 Construct the Classifier Group 
            x         : input to the classifier
            n_classes : number of output classes
            dropout   : percentage for dropout rate
        
Construct the Classifier Group
x         : input to the classifier
n_classes : number of output classes
dropout   : percentage for dropout rate
Construct the Classifier Group x : input to the classifier n_classes : number of output classes dropout : percentage for dropout rate
def classifier(self, x, n_classes, dropout=0.4):
        self.encoding = x
        x = AveragePooling2D((7, 7))(x)
        x = Flatten()(x)
        self.embedding = x
        outputs = super().classifier(x, n_classes, pooling=None, dropout=dropout)
        return outputs
def classifier ( self , x , n_classes , dropout = 0.4 ) : self . encoding = x x = AveragePooling2D ( ( 7 , 7 ) ) ( x ) x = Flatten ( ) ( x ) self . embedding = x outputs = super ( ) . classifier ( x , n_classes , pooling = None , dropout = dropout ) return outputs
Construct the Classifier Group
x         : input to the classifier
n_classes : number of output classes
dropout   : percentage for dropout rate
Construct the Classifier Group x : input to the classifier n_classes : number of output classes dropout : percentage for dropout rate
""" Construct the Classifier Group 
            x         : input to the classifier
            n_classes : number of output classes
            dropout   : percentage for dropout rate
        """ # Save the encoding layer # Pool at the end of all the convolutional residual blocks # Save the embedding layer
self
x
n_classes
dropout