6f528bb277012ec96bae86c30ef1dbd5eb3c2130,tensorlayer/layers.py,DropconnectDenseLayer,__init__,#DropconnectDenseLayer#Any#Any#Any#Any#Any#Any#Any#Any#Any#,752

Before Change

        self.n_units = n_units
        print("  tensorlayer:Instantiate DropconnectDenseLayer %s: %d, %s" % (self.name, self.n_units, act))

        W = tf.Variable(W_init(shape=(n_in, n_units), **W_init_args), name="W")
        b = tf.Variable(b_init(shape=[n_units], **b_init_args), name="b")
        self.outputs = act(tf.matmul(self.inputs, W) + b)

        set_keep[name] = tf.placeholder(tf.float32)
        W_dropcon = tf.nn.dropout(W,  set_keep[name])
        self.outputs = act(tf.matmul(self.inputs, W_dropcon) + b)

        self.all_layers = list(layer.all_layers)
        self.all_params = list(layer.all_params)

After Change

        self.n_units = n_units
        print("  tensorlayer:Instantiate DropconnectDenseLayer %s: %d, %s" % (self.name, self.n_units, act))

        with tf.variable_scope(name) as vs:
            // W = tf.Variable(W_init(shape=(n_in, n_units), **W_init_args), name="W")
            // b = tf.Variable(b_init(shape=[n_units], **b_init_args), name="b")
            W = tf.get_variable(name="W", shape=(n_in, n_units), initializer=W_init, **W_init_args )
            b = tf.get_variable(name="b", shape=(n_units), initializer=b_init, **b_init_args )
        self.outputs = act(tf.matmul(self.inputs, W) + b)

        set_keep[name] = tf.placeholder(tf.float32)
        W_dropcon = tf.nn.dropout(W,  set_keep[name])
        self.outputs = act(tf.matmul(self.inputs, W_dropcon) + b)

        self.all_layers = list(layer.all_layers)
        self.all_params = list(layer.all_params)

Instances