예제 #1
0
    def initialise_network(self):
        print("Initializing network")
        #IMPORTING REGULARIZERS w AND b
        w_regularizer = None
        b_regularizer = None
        reg_type = self.net_param.reg_type.lower()
        decay = self.net_param.decay
        if reg_type == 'l2' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l2_regularizer(decay)
            b_regularizer = regularizers.l2_regularizer(decay)
        elif reg_type == 'l1' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l1_regularizer(decay)
            b_regularizer = regularizers.l1_regularizer(decay)

        #---------W_INI = "he_normal", -- application_factory.py
        w_ini= InitializerFactory.get_initializer(name=self.net_param.weight_initializer)

        print("wWwWwWwWwWWWWWWwWWWWWWWWWweight_initializer; ", self.net_param.weight_initializer)
        print("NNNNNNNNname of application: ", self.net_param.name)

        #SELF.NET_PARAM.NAME = DENSE_VET 
        #Create dense_vnet and initialize with regularizers and activ funcs.
        self.net = ApplicationNetFactory.create(self.net_param.name)(
            num_classes=self.segmentation_param.num_classes,
            w_initializer=w_ini,
            b_initializer=InitializerFactory.get_initializer(
                name=self.net_param.bias_initializer),
            w_regularizer=w_regularizer,
            b_regularizer=b_regularizer,
            acti_func=self.net_param.activation_function)
예제 #2
0
    def initialise_network(self):
        '''
        Initialise the network and specifies the ordering of elements
        :return:
        '''
        w_regularizer = None
        b_regularizer = None
        reg_type = self.net_param.reg_type.lower()
        decay = self.net_param.decay
        if reg_type == 'l2' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l2_regularizer(decay)
            b_regularizer = regularizers.l2_regularizer(decay)
        elif reg_type == 'l1' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l1_regularizer(decay)
            b_regularizer = regularizers.l1_regularizer(decay)

        self.net = ApplicationNetFactory.create(
            'niftynet.contrib.csv_reader.toynet_features.ToyNetFeat')(
                num_classes=self.segmentation_param.num_classes,
                w_initializer=InitializerFactory.get_initializer(
                    name=self.net_param.weight_initializer),
                b_initializer=InitializerFactory.get_initializer(
                    name=self.net_param.bias_initializer),
                w_regularizer=w_regularizer,
                b_regularizer=b_regularizer,
                acti_func=self.net_param.activation_function)
        self.net_multi = ApplicationNetFactory.create(
            'niftynet.contrib.csv_reader.class_seg_finnet.ClassSegFinnet')(
                num_classes=self.segmentation_param.num_classes,
                w_initializer=InitializerFactory.get_initializer(
                    name=self.net_param.weight_initializer),
                b_initializer=InitializerFactory.get_initializer(
                    name=self.net_param.bias_initializer),
                w_regularizer=w_regularizer,
                b_regularizer=b_regularizer,
                acti_func=self.net_param.activation_function)
    def initialise_network(self):
        w_regularizer = None
        b_regularizer = None
        reg_type = self.net_param.reg_type.lower()
        decay = self.net_param.decay
        if reg_type == 'l2' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l2_regularizer(decay)
            b_regularizer = regularizers.l2_regularizer(decay)
        elif reg_type == 'l1' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l1_regularizer(decay)
            b_regularizer = regularizers.l1_regularizer(decay)

        self.net = ApplicationNetFactory.create(self.net_param.name)(
            num_classes=self.segmentation_param.num_classes,
            w_initializer=InitializerFactory.get_initializer(
                name=self.net_param.weight_initializer),
            b_initializer=InitializerFactory.get_initializer(
                name=self.net_param.bias_initializer),
            w_regularizer=w_regularizer,
            b_regularizer=b_regularizer,
            acti_func=self.net_param.activation_function)
    def initialise_network(self):
        w_regularizer = None
        b_regularizer = None
        reg_type = self.net_param.reg_type.lower()
        decay = self.net_param.decay
        if reg_type == 'l2' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l2_regularizer(decay)
            b_regularizer = regularizers.l2_regularizer(decay)
        elif reg_type == 'l1' and decay > 0:
            from tensorflow.contrib.layers.python.layers import regularizers
            w_regularizer = regularizers.l1_regularizer(decay)
            b_regularizer = regularizers.l1_regularizer(decay)

        self.net = ApplicationNetFactory.create(self.net_param.name)(
            num_classes=self.classification_param.num_classes,
            w_initializer=InitializerFactory.get_initializer(
                name=self.net_param.weight_initializer),
            b_initializer=InitializerFactory.get_initializer(
                name=self.net_param.bias_initializer),
            w_regularizer=w_regularizer,
            b_regularizer=b_regularizer,
            acti_func=self.net_param.activation_function)