utils.py 文件源码

def fully_connected( inputs , outputs_dim ,  he_init = False , activation_fn = None , regularization_scale = 0.0   ):
    x = layers.flatten( inputs )
    fan_in = x.get_shape()[-1].value
    fan_out = ( C + outputsdim ) / 2
    avg_fan = ( fan_in + fan_out ) / 2 
    if he_init:
        var = 2.0/avg_fan
    else:
        var = 1.0/avg_fan
    # var = (b - a)**2 / 12 , b==-a ,  (zero mean)
    upper_bound = np.sqrt( 12.0 * var ) *0.5
    weights_initializer = tf.random_uniform_initializer( -upper_bound , upper_bound , seed = None , dtype = tf.float32 )
    weights_regularizer = layers.l2_regularizer( scale = regularization_scale )
    return layers.fully_connected( x , outputs_dim , weights_initializer =  weights_initializer , activation_fn = activation_fn   ,   weights_regularizer = weights_regularizer )