utils.py 文件源码

def conv2d_transpose( inputs , outputs_dim , kernel_size , stride , padding = "SAME" , he_init = False , activation_fn = None , regularization_scale = 0.0   ):
    C = inputs.get_shape()[-1].value
    fan_in = C * kernel_size**2 / stride**2
    fan_out = C * kernel_size**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.conv2d_transpose( inputs , outputs_dim , kernel_size = kernel_size , stride = stride , padding = padding ,  weights_initializer = weights_initializer ,  activation_fn = activation_fn , weights_regularizer = weights_regularizer )