Networks.py 文件源码

def __init__(self, output_dim, init='glorot_uniform',
                 activation='linear', weights=None,
                 W_regularizer=None, b_regularizer=None, activity_regularizer=None,
                 W_constraint=None, b_constraint=None,
                 bias=False, input_dim=None, dale_ratio = .8, **kwargs):
        self.init = initializations.get(init)
        self.activation = activations.get(activation)
        self.output_dim = output_dim
        self.input_dim = input_dim

        self.W_regularizer = regularizers.get(W_regularizer)
        self.b_regularizer = regularizers.get(b_regularizer)
        self.activity_regularizer = regularizers.get(activity_regularizer)

        self.W_constraint = constraints.get(W_constraint)
        self.b_constraint = constraints.get(b_constraint)

        self.bias = bias
        self.initial_weights = weights
        self.input_spec = [InputSpec(ndim=2)]

        # OUR CHANGE
        self.dale_ratio = dale_ratio
        if dale_ratio:
            dale_vec = np.ones((input_dim, 1))
            dale_vec[int(dale_ratio*input_dim):, 0] = 0
            self.Dale = K.variable(dale_vec)

        if self.input_dim:
            kwargs['input_shape'] = (self.input_dim,)

        super(Dense, self).__init__(**kwargs)