tf.Module

Base neural network module class.

Used in the notebooks

Used in the guide Used in the tutorials

A module is a named container for tf.Variables, other tf.Modules and functions which apply to user input. For example a dense layer in a neural network might be implemented as a tf.Module:

 class Dense(tf.Module):
   def __init__(self, in_features, out_features, name=None):
     super(Dense, self).__init__(name=name)
     self.w = tf.Variable(
       tf.random.normal([in_features, out_features]), name='w')
     self.b = tf.Variable(tf.zeros([out_features]), name='b')
   def __call__(self, x):
     y = tf.matmul(x, self.w) + self.b