message: Updating tf.lookup documentation to use public symbols.
diff: @@ -821,7 +821,7 @@ def _as_string(tensor):
  class IdTableWithHashBuckets(LookupInterface):
  - """String to Id table wrapper that assigns out-of-vocabulary keys to buckets.
  + r"""String to Id table wrapper that assigns out-of-vocabulary keys to buckets.
  For example, if an instance of `IdTableWithHashBuckets` is initialized with a
  string-to-id table that maps:
  @@ -850,7 +850,14 @@ class IdTableWithHashBuckets(LookupInterface):
  num_oov_buckets = 3
  input_tensor = tf.constant(["emerson", "lake", "palmer", "king", "crimnson"])
  table = tf.IdTableWithHashBuckets(
  - tf.StaticHashTable(tf.TextFileIdTableInitializer(filename),
  + tf.StaticHashTable(
  + tf.lookup.TextFileInitializer(
  + filename,
  + key_dtype=tf.string,
  + key_index=tf.lookup.TextFileIndex.WHOLE_LINE,
  + value_dtype=tf.int64,
  + value_index=tf.lookup.TextFileIndex.LINE_NUMBER,
  + delimiter="\t"),
  default_value),
  num_oov_buckets)
  out = table.lookup(input_tensor).
  @@ -1029,7 +1036,7 @@ class IdTableWithHashBuckets(LookupInterface):
  @tf_export("lookup.StaticVocabularyTable", v1=[])
  class StaticVocabularyTable(LookupInterface):
  - """String to Id table wrapper that assigns out-of-vocabulary keys to buckets.
  + r"""String to Id table wrapper that assigns out-of-vocabulary keys to buckets.
  For example, if an instance of `StaticVocabularyTable` is initialized with a
  string-to-id initializer that maps:
  @@ -1058,7 +1065,12 @@ class StaticVocabularyTable(LookupInterface):
  num_oov_buckets = 3
  input_tensor = tf.constant(["emerson", "lake", "palmer", "king", "crimnson"])
  table = tf.lookup.StaticVocabularyTable(
  - tf.TextFileIdTableInitializer(filename), num_oov_buckets)
  + tf.lookup.TextFileInitializer(
  + filename,
  + key_dtype=tf.string, key_index=tf.lookup.TextFileIndex.WHOLE_LINE,
  + value_dtype=tf.int64, value_index=tf.lookup.TextFileIndex.LINE_NUMBER,
  + delimiter="\t"),
  + num_oov_buckets)
  out = table.lookup(input_tensor).
  table.init.run()
  print(out.eval())
  