我一直在使用 BERT large uncased 进行二进制文本分类。我正在使用 google colab 进行训练模型。为了保存估算器，我使用了以下方法serving_input_funtion：
def serving_input_receiver_fn():
with tf.variable_scope("foo"):
feature_spec = {
"input_ids": tf.FixedLenFeature([128], tf.int64),
"input_mask": tf.FixedLenFeature([128], tf.int64),
"segment_ids": tf.FixedLenFeature([128], tf.int64),
"label_ids": tf.FixedLenFeature([], tf.int64),
}
serialized_tf_example = tf.placeholder(dtype=tf.string, shape=None,
name='input_example_tensor')
receiver_tensors = {'examples': serialized_tf_example}
features = tf.parse_example(serialized_tf_example, feature_spec)
return tf.estimator.export.ServingInputReceiver(features, receiver_tensors)
并保存了以下估算器：
estimator._export_to_tpu = False
estimator.export_saved_model(export_dir_base = "/bert_0.3/",serving_input_receiver_fn = serving_input_receiver_fn)
这保存了估计器，但现在当我试图用来saved_model_cli测试估计器时，它不起作用。它向我抛出错误，例如：
ValueError: Type <class 'bytes'> for value b'\n\x12\n\x10\n\x08sentence\x12\x04\n\x02\n\x00' is not supported for tf.train.Feature.
命令是：
saved_model_cli run --dir '/bert_0.3/1564572852' --tag_set serve --signature_def serving_default --input_examples '"examples"=[{"input_ids":[b"\n\x12\n\x10\n\x08sentence\x12\x04\n\x02\n\x00"],"input_mask":[b"\n-\n+\n\x08sentence\x12\x1f\n\x1d\n\x1bThis API is a little tricky"],"segment_ids":[None],"label_ids":["label_1"]}]'
它不直接接受字符串，所以这就是我手动将其划分为dict. 将其转换为 后dict，我意识到这仅接受bytes_list. 这就是我将字符串转换为字节格式的原因。
堆栈跟踪
File "/usr/local/bin/saved_model_cli", line 8, in <module>
sys.exit(main())
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py", line 990, in main
args.func(args)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py", line 724, in run
init_tpu=args.init_tpu, tf_debug=args.tf_debug)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/tools/saved_model_cli.py", line 420, in run_saved_model_with_feed_dict
loader.load(sess, tag_set.split(','), saved_model_dir)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/loader_impl.py", line 269, in load
return loader.load(sess, tags, import_scope, **saver_kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/loader_impl.py", line 423, in load
self.restore_variables(sess, saver, import_scope)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/saved_model/loader_impl.py", line 377, in restore_variables
saver.restore(sess, self._variables_path)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/training/saver.py", line 1290, in restore
{self.saver_def.filename_tensor_name: save_path})
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InternalError: Dst tensor is not initialized.
[[node save_2/RestoreV2 (defined at /lib/python2.7/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
如果有人能告诉我哪里出了问题，我们将不胜感激。serving_input_receiver_fn我猜也可能有问题。
最大序列长度为 128
谢谢。
编辑 1：
如果使用 tf.placeholder() 而不是 tf.FixedLenFeature
