class_docstr: Id to dense vector embedding.
code: def __init__(
      self,
      max_id,
      dim,
      initializer=lambda: tf.truncated_normal_initializer(stddev=0.1),
      **kwargs,
  ):
      super(Embedding, self).__init__(**kwargs)
      self.max_id = max_id
      self.dim = dim
      self.initializer = initializer
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import tensorflow
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 to create a new Embedding object from inherited base classes: Layer with example: obj = Embedding(max_id, dim, initializer)