tf.layers.dense

dense全连接层,相当于添加一个层

tf.layers.dense(
    inputs,                                 # 输入此网络的数据
    units,                                  # 输出维度大小,改变inputs的最后一维
    activation=None,                        # 激活函数
    use_bias=True,                          #是否使用偏置项
    kernel_initializer=None,                # 权重初始化if True initializer used by `tf.get_variable`.
    bias_initializer=init_ops.zeros_initializer(),     # 偏差初始化
    kernel_regularizer=None,                # 权重正则化
    bias_regularizer=None,                  # 偏差正则化
    activity_regularizer=None,              # 输出的正则化
    kernel_constraint=None,                 # 
    bias_constraint=None,
    trainable=True,                         # 该层是否参与训练if `True` also add variables to the graph collection ‘GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
    name=None,                              # 该层的名字
    reuse=None)                             # 是否重复使用参数
# outputs = activation(inputs * kernel + bias)
# `kernel` is a weights matrix created by the layer
# `bias` is a bias vector created by the layer  (only if `use_bias` is `True`).

你可能感兴趣的:(tf.layers.dense)