original_docstring:  create lookup table to translate item index to item id.
          
          Args:
              file_path (str): Path to txt file containing item ids.
              
          Returns:
              (tf.lookup.StaticVocabularyTable): The lookup table.
          
docstring: create lookup table to translate item index to item id.
docstring_tokens: create lookup table to translate item index to item id .
code: def create_item_id_table(self, file_path):
          """ create lookup table to translate item index to item id.
          
          Args:
              file_path (str): Path to txt file containing item ids.
              
          Returns:
              (tf.lookup.StaticVocabularyTable): The lookup table.
          """
          values = tf.strings.split(tf.io.read_file(file_path), '\n')
          keys = tf.range(values.shape[0], dtype=tf.int32)
          initializer = tf.lookup.KeyValueTensorInitializer(keys=keys, values=values, key_dtype=tf.int32, value_dtype=tf.string)
          table = tf.lookup.StaticHashTable(initializer, default_value='unknown')
          return table
code_tokens: def create_item_id_table ( self , file_path ) : values = tf . strings . split ( tf . io . read_file ( file_path ) , '\n' ) keys = tf . range ( values . shape [ 0 ] , dtype = tf . int32 ) initializer = tf . lookup . KeyValueTensorInitializer ( keys = keys , values = values , key_dtype = tf . int32 , value_dtype = tf . string ) table = tf . lookup . StaticHashTable ( initializer , default_value = 'unknown' ) return table
short_docstring: create lookup table to translate item index to item id.
short_docstring_tokens: create lookup table to translate item index to item id .
comment: """ create lookup table to translate item index to item id.
          
          Args:
              file_path (str): Path to txt file containing item ids.
              
          Returns:
              (tf.lookup.StaticVocabularyTable): The lookup table.
          """