parameters: (self, sparse_tensors, weight_collections,
                                       trainable)
return_statement: return self._get_dense_tensor_internal_helper(sparse_tensors,
                                                    embedding_weights)
docstring: Private method that follows the signature of _get_dense_tensor.
docstring_summary: Private method that follows the signature of _get_dense_tensor.
docstring_tokens: Private method that follows the signature of _get_dense_tensor .
function: def _old_get_dense_tensor_internal(self, sparse_tensors, weight_collections,
                                       trainable):
      """Private method that follows the signature of _get_dense_tensor."""
      embedding_shape = (self.categorical_column._num_buckets, self.dimension)  # pylint: disable=protected-access
      if (weight_collections and
          ops.GraphKeys.GLOBAL_VARIABLES not in weight_collections):
        weight_collections.append(ops.GraphKeys.GLOBAL_VARIABLES)
      embedding_weights = variable_scope.get_variable(
          name='embedding_weights',
          shape=embedding_shape,
          dtype=dtypes.float32,
          initializer=self.initializer,
          trainable=self.trainable and trainable,
          collections=weight_collections)
      return self._get_dense_tensor_internal_helper(sparse_tensors,
                                                    embedding_weights)
function_tokens: def _old_get_dense_tensor_internal ( self , sparse_tensors , weight_collections , trainable ) : embedding_shape = ( self . categorical_column . _num_buckets , self . dimension ) # pylint: disable=protected-access if ( weight_collections and ops . GraphKeys . GLOBAL_VARIABLES not in weight_collections ) : weight_collections . append ( ops . GraphKeys . GLOBAL_VARIABLES ) embedding_weights = variable_scope . get_variable ( name = 'embedding_weights' , shape = embedding_shape , dtype = dtypes . float32 , initializer = self . initializer , trainable = self . trainable and trainable , collections = weight_collections ) return self . _get_dense_tensor_internal_helper ( sparse_tensors , embedding_weights )