class_docstr: Operator adding input embedding to the given cell.
  
  Note: in many cases it may be more efficient to not use this wrapper,
  but instead concatenate the whole sequence of your inputs in time,
  do the embedding on this batch-concatenated sequence, then split it and
  feed into your RNN.
docstr: Run the cell on embedded inputs.
docstr_tok: ["Run","the","cell","on","embedded","inputs","."]
code: def call(self, inputs, state):
      """Run the cell on embedded inputs."""
      with ops.device("/cpu:0"):
          if self._initializer:
              initializer = self._initializer
          elif vs.get_variable_scope().initializer:
              initializer = vs.get_variable_scope().initializer
          else:
              # Default initializer for embeddings should have variance=1.
              sqrt3 = math.sqrt(
                  3
              )  # Uniform(-sqrt(3), sqrt(3)) has variance=1.
              initializer = init_ops.random_uniform_initializer(
                  -sqrt3, sqrt3
              )
  
          if isinstance(state, tuple):
              data_type = state[0].dtype
          else:
              data_type = state.dtype
  
          embedding = vs.get_variable(
              "embedding",
              [self._embedding_classes, self._embedding_size],
              initializer=initializer,
              dtype=data_type,
          )
          embedded = embedding_ops.embedding_lookup(
              embedding, array_ops.reshape(inputs, [-1])
          )
  
          return self._cell(embedded, state)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import rnn_cell_impl
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
label_desc: Use image node_id 5 for calling the EmbeddingWrapper obj's underlying member method code with example usage: obj.call(inputs, state) and returns: self