本文整理匯總了Python中syntaxnet.ops.gen_parser_ops.document_sink方法的典型用法代碼示例。如果您正苦於以下問題：Python gen_parser_ops.document_sink方法的具體用法？Python gen_parser_ops.document_sink怎麽用？Python gen_parser_ops.document_sink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syntaxnet.ops.gen_parser_ops的用法示例。
在下文中一共展示了gen_parser_ops.document_sink方法的1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: main
# 需要導入模塊: from syntaxnet.ops import gen_parser_ops [as 別名]
# 或者: from syntaxnet.ops.gen_parser_ops import document_sink [as 別名]
def main(unused_argv):
logging.set_verbosity(logging.INFO)
if not gfile.IsDirectory(OutputPath('')):
gfile.MakeDirs(OutputPath(''))
# Rewrite context.
RewriteContext()
# Creates necessary term maps.
if FLAGS.compute_lexicon:
logging.info('Computing lexicon...')
with tf.Session(FLAGS.tf_master) as sess:
gen_parser_ops.lexicon_builder(task_context=OutputPath('context'),
corpus_name=FLAGS.training_corpus).run()
with tf.Session(FLAGS.tf_master) as sess:
feature_sizes, domain_sizes, embedding_dims, num_actions = sess.run(
gen_parser_ops.feature_size(task_context=OutputPath('context'),
arg_prefix=FLAGS.arg_prefix))
# Well formed and projectivize.
if FLAGS.projectivize_training_set:
logging.info('Preprocessing...')
with tf.Session(FLAGS.tf_master) as sess:
source, last = gen_parser_ops.document_source(
task_context=OutputPath('context'),
batch_size=FLAGS.batch_size,
corpus_name=FLAGS.training_corpus)
sink = gen_parser_ops.document_sink(
task_context=OutputPath('context'),
corpus_name='projectivized-training-corpus',
documents=gen_parser_ops.projectivize_filter(
gen_parser_ops.well_formed_filter(source,
task_context=OutputPath(
'context')),
task_context=OutputPath('context')))
while True:
tf_last, _ = sess.run([last, sink])
if tf_last:
break
logging.info('Training...')
with tf.Session(FLAGS.tf_master) as sess:
Train(sess, num_actions, feature_sizes, domain_sizes, embedding_dims)