Python eval_trec.evaluate方法代码示例

本文整理汇总了Python中skipthoughts.eval_trec.evaluate方法的典型用法代码示例。如果您正苦于以下问题：Python eval_trec.evaluate方法的具体用法？Python eval_trec.evaluate怎么用？Python eval_trec.evaluate使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类skipthoughts.eval_trec的用法示例。

在下文中一共展示了eval_trec.evaluate方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: main

# 需要导入模块: from skipthoughts import eval_trec [as 别名]
# 或者: from skipthoughts.eval_trec import evaluate [as 别名]
def main(unused_argv):
  if not FLAGS.data_dir:
    raise ValueError("--data_dir is required.")

  encoder = encoder_manager.EncoderManager()

  # Maybe load unidirectional encoder.
  if FLAGS.uni_checkpoint_path:
    print("Loading unidirectional model...")
    uni_config = configuration.model_config()
    encoder.load_model(uni_config, FLAGS.uni_vocab_file,
                       FLAGS.uni_embeddings_file, FLAGS.uni_checkpoint_path)

  # Maybe load bidirectional encoder.
  if FLAGS.bi_checkpoint_path:
    print("Loading bidirectional model...")
    bi_config = configuration.model_config(bidirectional_encoder=True)
    encoder.load_model(bi_config, FLAGS.bi_vocab_file, FLAGS.bi_embeddings_file,
                       FLAGS.bi_checkpoint_path)

  if FLAGS.eval_task in ["MR", "CR", "SUBJ", "MPQA"]:
    eval_classification.eval_nested_kfold(
        encoder, FLAGS.eval_task, FLAGS.data_dir, use_nb=False)
  elif FLAGS.eval_task == "SICK":
    eval_sick.evaluate(encoder, evaltest=True, loc=FLAGS.data_dir)
  elif FLAGS.eval_task == "MSRP":
    eval_msrp.evaluate(
        encoder, evalcv=True, evaltest=True, use_feats=True, loc=FLAGS.data_dir)
  elif FLAGS.eval_task == "TREC":
    eval_trec.evaluate(encoder, evalcv=True, evaltest=True, loc=FLAGS.data_dir)
  else:
    raise ValueError("Unrecognized eval_task: %s" % FLAGS.eval_task)

  encoder.close()

开发者ID:ringringyi，项目名称:DOTA_models，代码行数:36，代码来源:evaluate.py

示例2: main

# 需要导入模块: from skipthoughts import eval_trec [as 别名]
# 或者: from skipthoughts.eval_trec import evaluate [as 别名]
def main(unused_argv):
    if not FLAGS.data_dir:
        raise ValueError("--data_dir is required.")

    encoder = encoder_manager.EncoderManager()

    # Maybe load unidirectional encoder.
    if FLAGS.uni_checkpoint_path:
        print("Loading unidirectional model...")
        uni_config = configuration.model_config()
        encoder.load_model(uni_config, FLAGS.uni_vocab_file,
                           FLAGS.uni_embeddings_file, FLAGS.uni_checkpoint_path)

    # Maybe load bidirectional encoder.
    if FLAGS.bi_checkpoint_path:
        print("Loading bidirectional model...")
        bi_config = configuration.model_config(bidirectional_encoder=True)
        encoder.load_model(bi_config, FLAGS.bi_vocab_file,
                           FLAGS.bi_embeddings_file,
                           FLAGS.bi_checkpoint_path)

    if FLAGS.eval_task in ["MR", "CR", "SUBJ", "MPQA"]:
        eval_classification.eval_nested_kfold(
            encoder, FLAGS.eval_task, FLAGS.data_dir, use_nb=False)
    elif FLAGS.eval_task == "SICK":
        eval_sick.evaluate(encoder, evaltest=True, loc=FLAGS.data_dir)
    elif FLAGS.eval_task == "MSRP":
        eval_msrp.evaluate(
            encoder, evalcv=True, evaltest=True, use_feats=True,
            loc=FLAGS.data_dir)
    elif FLAGS.eval_task == "TREC":
        eval_trec.evaluate(encoder, evalcv=True, evaltest=True,
                           loc=FLAGS.data_dir)
    else:
        raise ValueError("Unrecognized eval_task: %s" % FLAGS.eval_task)

    encoder.close()

开发者ID:snuspl，项目名称:parallax，代码行数:39，代码来源:evaluate.py

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