class_docstr: A Keras Layer for Dynamic Embedding Lookup.
  
  This is useful when the gradient descent update is required for embedding
  lookup. The input of this layer is a `Tensor` of string keys and it outputs
  the embedding output as a float `Tensor`.
class_docstr_tok: ["A","Keras","Layer","for","Dynamic","Embedding","Lookup",".","This","is","useful","when","the","gradient","descent","update","is","required","for","embedding","lookup",".","The","input","of","this","layer","is","a","`","Tensor","`","of","string","keys","and","it","outputs","the","embedding","output","as","a","float","`","Tensor","`","."]
code: def call(self, keys):
      return gen_carls_ops.dynamic_embedding_lookup(
          keys,
          self.grad_placeholder,
          self.resource,
          self.embedding_dimension,
      )
  
file_path: neural-structured-learning/research/carls/dynamic_embedding_ops.py
imports: import typing
  from research.carls import context
  from research.carls import dynamic_embedding_config_pb2
  from research.carls.kernels import gen_carls_ops
  import tensorflow
label_desc: Use image node_id 3 for calling the DynamicEmbeddingLookup obj's underlying member method code with example usage: obj.call(keys) and returns: gen_carls_ops