Python lookup_ops.index_to_string_table_from_tensor方法代碼示例

本文整理匯總了Python中tensorflow.python.ops.lookup_ops.index_to_string_table_from_tensor方法的典型用法代碼示例。如果您正苦於以下問題：Python lookup_ops.index_to_string_table_from_tensor方法的具體用法？Python lookup_ops.index_to_string_table_from_tensor怎麽用？Python lookup_ops.index_to_string_table_from_tensor使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.ops.lookup_ops的用法示例。

在下文中一共展示了lookup_ops.index_to_string_table_from_tensor方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: _class_string_table

# 需要導入模塊: from tensorflow.python.ops import lookup_ops [as 別名]
# 或者: from tensorflow.python.ops.lookup_ops import index_to_string_table_from_tensor [as 別名]
def _class_string_table(self):
    """Creates a lookup table for class_string.

    In eager execution, this lookup table will be lazily created on the first
    call of `self._class_string_table` and cached for later use; In graph
    execution, it will be created on demand.

    Returns:
      A hash table for lookup.
    """
    if (self._cached_class_string_table is None or not tf.executing_eagerly()):
      self._cached_class_string_table = (
          lookup_ops.index_to_string_table_from_tensor(
              vocabulary_list=self._label_vocabulary,
              name='class_string_lookup'))
    return self._cached_class_string_table

開發者ID:tensorflow，項目名稱:estimator，代碼行數:18，代碼來源:binary_class_head.py

示例2: create_test_iterator

# 需要導入模塊: from tensorflow.python.ops import lookup_ops [as 別名]
# 或者: from tensorflow.python.ops.lookup_ops import index_to_string_table_from_tensor [as 別名]
def create_test_iterator(hparams, mode):
  """Create test iterator."""
  src_vocab_table = lookup_ops.index_table_from_tensor(
      tf.constant([hparams.eos, "a", "b", "c", "d"]))
  tgt_vocab_mapping = tf.constant([hparams.sos, hparams.eos, "a", "b", "c"])
  tgt_vocab_table = lookup_ops.index_table_from_tensor(tgt_vocab_mapping)
  if mode == tf.contrib.learn.ModeKeys.INFER:
    reverse_tgt_vocab_table = lookup_ops.index_to_string_table_from_tensor(
        tgt_vocab_mapping)

  src_dataset = tf.contrib.data.Dataset.from_tensor_slices(
      tf.constant(["a a b b c", "a b b"]))

  if mode != tf.contrib.learn.ModeKeys.INFER:
    tgt_dataset = tf.contrib.data.Dataset.from_tensor_slices(
        tf.constant(["a b c b c", "a b c b"]))
    return (
        iterator_utils.get_iterator(
            src_dataset=src_dataset,
            tgt_dataset=tgt_dataset,
            src_vocab_table=src_vocab_table,
            tgt_vocab_table=tgt_vocab_table,
            batch_size=hparams.batch_size,
            sos=hparams.sos,
            eos=hparams.eos,
            source_reverse=hparams.source_reverse,
            random_seed=hparams.random_seed,
            num_buckets=hparams.num_buckets),
        src_vocab_table,
        tgt_vocab_table)
  else:
    return (
        iterator_utils.get_infer_iterator(
            src_dataset=src_dataset,
            src_vocab_table=src_vocab_table,
            eos=hparams.eos,
            source_reverse=hparams.source_reverse,
            batch_size=hparams.batch_size),
        src_vocab_table,
        tgt_vocab_table,
        reverse_tgt_vocab_table)

開發者ID:steveash，項目名稱:NETransliteration-COLING2018，代碼行數:43，代碼來源:common_test_utils.py

示例3: create_test_iterator

# 需要導入模塊: from tensorflow.python.ops import lookup_ops [as 別名]
# 或者: from tensorflow.python.ops.lookup_ops import index_to_string_table_from_tensor [as 別名]
def create_test_iterator(hparams, mode):
  """Create test iterator."""
  src_vocab_table = lookup_ops.index_table_from_tensor(
      tf.constant([hparams.eos, "a", "b", "c", "d"]))
  tgt_vocab_mapping = tf.constant([hparams.sos, hparams.eos, "a", "b", "c"])
  tgt_vocab_table = lookup_ops.index_table_from_tensor(tgt_vocab_mapping)
  if mode == tf.contrib.learn.ModeKeys.INFER:
    reverse_tgt_vocab_table = lookup_ops.index_to_string_table_from_tensor(
        tgt_vocab_mapping)

  src_dataset = tf.data.Dataset.from_tensor_slices(
      tf.constant(["a a b b c", "a b b"]))

  if mode != tf.contrib.learn.ModeKeys.INFER:
    tgt_dataset = tf.data.Dataset.from_tensor_slices(
        tf.constant(["a b c b c", "a b c b"]))
    return (
        iterator_utils.get_iterator(
            src_dataset=src_dataset,
            tgt_dataset=tgt_dataset,
            src_vocab_table=src_vocab_table,
            tgt_vocab_table=tgt_vocab_table,
            batch_size=hparams.batch_size,
            sos=hparams.sos,
            eos=hparams.eos,
            random_seed=hparams.random_seed,
            num_buckets=hparams.num_buckets),
        src_vocab_table,
        tgt_vocab_table)
  else:
    return (
        iterator_utils.get_infer_iterator(
            src_dataset=src_dataset,
            src_vocab_table=src_vocab_table,
            eos=hparams.eos,
            batch_size=hparams.batch_size),
        src_vocab_table,
        tgt_vocab_table,
        reverse_tgt_vocab_table)

開發者ID:snuspl，項目名稱:parallax，代碼行數:41，代碼來源:common_test_utils.py

示例4: create_test_iterator

# 需要導入模塊: from tensorflow.python.ops import lookup_ops [as 別名]
# 或者: from tensorflow.python.ops.lookup_ops import index_to_string_table_from_tensor [as 別名]
def create_test_iterator(hparams, mode, trie_excludes=None):
  """Create test iterator."""
  src_vocab_table = lookup_ops.index_table_from_tensor(
      tf.constant([hparams.eos, "a", "b", "c", "d"]))
  tgt_vocab_mapping = tf.constant([hparams.sos, hparams.eos, "a", "b", "c"])
  tgt_vocab_table = lookup_ops.index_table_from_tensor(tgt_vocab_mapping)

  reverse_tgt_vocab_table = lookup_ops.index_to_string_table_from_tensor(
      tgt_vocab_mapping)

  src_dataset = tf.data.Dataset.from_tensor_slices(
      tf.constant(["a a b b c", "a b b"]))

  ctx_dataset = tf.data.Dataset.from_tensor_slices(
      tf.constant(["c b c b a", "b c b a"]))

  trie_excludes = trie_excludes or []
  trie_excludes = " {} ".format(hparams.eos).join(trie_excludes)
  tex_dataset = tf.data.Dataset.from_tensor_slices(
      tf.constant([trie_excludes, trie_excludes]))

  if mode != tf.contrib.learn.ModeKeys.INFER:
    tgt_dataset = tf.data.Dataset.from_tensor_slices(
        tf.constant(["a b c b c", "a b c b"]))
    return (iterator_utils.get_iterator(
        hparams=hparams,
        src_dataset=src_dataset,
        tgt_dataset=tgt_dataset,
        ctx_dataset=ctx_dataset,
        annot_dataset=None,
        src_vocab_table=src_vocab_table,
        tgt_vocab_table=tgt_vocab_table,
        batch_size=hparams.batch_size,
        sos=hparams.sos,
        eos=hparams.eos,
        random_seed=hparams.random_seed,
        num_buckets=hparams.num_buckets), src_vocab_table, tgt_vocab_table,
            reverse_tgt_vocab_table)
  else:
    return (iterator_utils.get_infer_iterator(
        hparams=hparams,
        src_dataset=src_dataset,
        ctx_dataset=ctx_dataset,
        annot_dataset=None,
        trie_exclude_dataset=tex_dataset,
        src_vocab_table=src_vocab_table,
        tgt_vocab_table=tgt_vocab_table,
        eos=hparams.eos,
        batch_size=hparams.batch_size), src_vocab_table, tgt_vocab_table,
            reverse_tgt_vocab_table)

開發者ID:google，項目名稱:active-qa，代碼行數:52，代碼來源:common_test_utils.py

注：本文中的tensorflow.python.ops.lookup_ops.index_to_string_table_from_tensor方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。