tf全连接dense的几个函数

嗨各位大佬好，我是小菜鸟。

tf中关于dense有几个函数(对象)，比如说下面的，但其实是一样的，只不过在tf2中只能用后者

tf.contrib.layers.fully_connected
tf.layers.dense
tf.keras.layers.Dense

For Recommendation in Deep learning QQ Group 102948747
For Visual in deep learning QQ Group 629530787
I'm here waiting for you 
不接受这个网页的私聊/私信！！
本宝宝长期征集真实情感经历（发在我公号：美好时光与你同行），长期接受付费咨询（啥问题都可），付费改代码。
 

>>> help(tf.layers.dense)
dense(inputs, units, activation=None, use_bias=True, kernel_initializer=None, bias_initializer=, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, trainable=True, name=None, reuse=None)
    Functional interface for the densely-connected layer. (deprecated)
    
    Use keras.layers.Dense instead.
    
    This layer implements the operation:
    `outputs = activation(inputs * kernel + bias)`
    where `activation` is the activation function passed as the `activation`
    argument (if not `None`), `kernel` is a weights matrix created by the layer,
    and `bias` is a bias vector created by the layer
    (only if `use_bias` is `True`).
    
    Arguments:
      inputs: Tensor input.
      units: Integer or Long, dimensionality of the output space.
      activation: Activation function (callable). Set it to None to maintain a
        linear activation.
      use_bias: Boolean, whether the layer uses a bias.
      kernel_initializer: Initializer function for the weight matrix.
        If `None` (default), weights are initialized using the default
        initializer used by `tf.compat.v1.get_variable`.
      bias_initializer: Initializer function for the bias.
      kernel_regularizer: Regularizer function for the weight matrix.
      bias_regularizer: Regularizer function for the bias.
      activity_regularizer: Regularizer function for the output.
      kernel_constraint: An optional projection function to be applied to the
          kernel after being updated by an `Optimizer` (e.g. used to implement
          norm constraints or value constraints for layer weights). The function
          must take as input the unprojected variable and must return the

>>> help(tf.keras.layers.Dense)
class Dense(tensorflow.python.keras.engine.base_layer.Layer)
 |  Dense(units, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs)
 |  
 |  Just your regular densely-connected NN layer.

那么可以将2替换为3，在分布式计算中dense中有参数要进行初始化，不能放在call下，一定要放在init中，这也是tf.AUTO_REUSE的意义。

愿我们终有重逢之时，而你还记得我们曾经讨论的话题。