Python generator_utils.UNSHUFFLED_SUFFIX屬性代碼示例

本文整理匯總了Python中tensor2tensor.data_generators.generator_utils.UNSHUFFLED_SUFFIX屬性的典型用法代碼示例。如果您正苦於以下問題：Python generator_utils.UNSHUFFLED_SUFFIX屬性的具體用法？Python generator_utils.UNSHUFFLED_SUFFIX怎麽用？Python generator_utils.UNSHUFFLED_SUFFIX使用的例子？那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在類tensor2tensor.data_generators.generator_utils的用法示例。

在下文中一共展示了generator_utils.UNSHUFFLED_SUFFIX屬性的5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: generate_data_for_problem

# 需要導入模塊: from tensor2tensor.data_generators import generator_utils [as 別名]
# 或者: from tensor2tensor.data_generators.generator_utils import UNSHUFFLED_SUFFIX [as 別名]
def generate_data_for_problem(problem):
  """Generate data for a problem in _SUPPORTED_PROBLEM_GENERATORS."""
  training_gen, dev_gen = _SUPPORTED_PROBLEM_GENERATORS[problem]

  num_shards = FLAGS.num_shards or 10
  tf.logging.info("Generating training data for %s.", problem)
  train_output_files = generator_utils.train_data_filenames(
      problem + generator_utils.UNSHUFFLED_SUFFIX, FLAGS.data_dir, num_shards)
  generator_utils.generate_files(training_gen(), train_output_files,
                                 FLAGS.max_cases)
  tf.logging.info("Generating development data for %s.", problem)
  dev_output_files = generator_utils.dev_data_filenames(
      problem + generator_utils.UNSHUFFLED_SUFFIX, FLAGS.data_dir, 1)
  generator_utils.generate_files(dev_gen(), dev_output_files)
  all_output_files = train_output_files + dev_output_files
  generator_utils.shuffle_dataset(all_output_files)

開發者ID:akzaidi，項目名稱:fine-lm，代碼行數:18，代碼來源:t2t_datagen.py

示例2: training_filepaths

# 需要導入模塊: from tensor2tensor.data_generators import generator_utils [as 別名]
# 或者: from tensor2tensor.data_generators.generator_utils import UNSHUFFLED_SUFFIX [as 別名]
def training_filepaths(self, data_dir, num_shards, shuffled):
    file_basename = self.dataset_filename()
    if not shuffled:
      file_basename += generator_utils.UNSHUFFLED_SUFFIX
    return generator_utils.train_data_filenames(file_basename, data_dir,
                                                num_shards)

開發者ID:akzaidi，項目名稱:fine-lm，代碼行數:8，代碼來源:problem.py

示例3: dev_filepaths

# 需要導入模塊: from tensor2tensor.data_generators import generator_utils [as 別名]
# 或者: from tensor2tensor.data_generators.generator_utils import UNSHUFFLED_SUFFIX [as 別名]
def dev_filepaths(self, data_dir, num_shards, shuffled):
    file_basename = self.dataset_filename()
    if not shuffled:
      file_basename += generator_utils.UNSHUFFLED_SUFFIX
    return generator_utils.dev_data_filenames(file_basename, data_dir,
                                              num_shards)

開發者ID:akzaidi，項目名稱:fine-lm，代碼行數:8，代碼來源:problem.py

示例4: test_filepaths

# 需要導入模塊: from tensor2tensor.data_generators import generator_utils [as 別名]
# 或者: from tensor2tensor.data_generators.generator_utils import UNSHUFFLED_SUFFIX [as 別名]
def test_filepaths(self, data_dir, num_shards, shuffled):
    file_basename = self.dataset_filename()
    if not shuffled:
      file_basename += generator_utils.UNSHUFFLED_SUFFIX
    return generator_utils.test_data_filenames(file_basename, data_dir,
                                               num_shards)

開發者ID:akzaidi，項目名稱:fine-lm，代碼行數:8，代碼來源:problem.py

示例5: generate_data_for_problem

# 需要導入模塊: from tensor2tensor.data_generators import generator_utils [as 別名]
# 或者: from tensor2tensor.data_generators.generator_utils import UNSHUFFLED_SUFFIX [as 別名]
def generate_data_for_problem(problem):
  """Generate data for a problem in _SUPPORTED_PROBLEM_GENERATORS."""
  training_gen, dev_gen, test_gen = _SUPPORTED_PROBLEM_GENERATORS[problem]

  num_train_shards = FLAGS.num_shards or 10
  tf.logging.info("Generating training data for %s.", problem)
  train_output_files = generator_utils.train_data_filenames(
      problem + generator_utils.UNSHUFFLED_SUFFIX, FLAGS.data_dir,
      num_train_shards)
  generator_utils.generate_files(training_gen(), train_output_files,
                                 FLAGS.max_cases)
  num_dev_shards = int(num_train_shards * 0.1)
  tf.logging.info("Generating development data for %s.", problem)
  dev_output_files = generator_utils.dev_data_filenames(
      problem + generator_utils.UNSHUFFLED_SUFFIX, FLAGS.data_dir,
      num_dev_shards)
  generator_utils.generate_files(dev_gen(), dev_output_files)
  num_test_shards = int(num_train_shards * 0.1)
  test_output_files = []
  test_gen_data = test_gen()
  if test_gen_data is not None:
    tf.logging.info("Generating test data for %s.", problem)
    test_output_files = generator_utils.test_data_filenames(
        problem + generator_utils.UNSHUFFLED_SUFFIX, FLAGS.data_dir,
        num_test_shards)
    generator_utils.generate_files(test_gen_data, test_output_files)
  all_output_files = train_output_files + dev_output_files + test_output_files
  generator_utils.shuffle_dataset(all_output_files)

開發者ID:tensorflow，項目名稱:tensor2tensor，代碼行數:30，代碼來源:t2t_datagen.py

注：本文中的tensor2tensor.data_generators.generator_utils.UNSHUFFLED_SUFFIX屬性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。