我想保存一个模型来对特定图片进行一些预测。这是我的服务功能：
def _serving_input_receiver_fn():
# Note: only handles one image at a time
feat = tf.placeholder(tf.float32, shape=[None, 120, 50, 1])
return tf.estimator.export.TensorServingInputReceiver(features=feat, receiver_tensors=feat)
这是我导出模型的地方：
export_dir_base = os.path.join(FLAGS.model_dir, 'export')
export_dir = estimator.export_savedmodel(
export_dir_base, _serving_input_receiver_fn)
但我收到以下错误：
ValueError: Both labels and logits must be provided.
现在这个错误我不明白，因为 Serving 的东西应该只创建一个占位符，以便我以后可以通过占位符放置一些图像以对保存的模型进行预测？
这是整个回溯：
Traceback (most recent call last):
File "/home/cezary/models/official/mnist/mnist_tpu.py", line 222, in <module>
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/home/cezary/models/official/mnist/mnist_tpu.py", line 206, in main
export_dir_base, _serving_input_receiver_fn)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 650, in export_savedmodel
mode=model_fn_lib.ModeKeys.PREDICT)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 703, in _export_saved_model_for_mode
strip_default_attrs=strip_default_attrs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 811, in _export_all_saved_models
mode=model_fn_lib.ModeKeys.PREDICT)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1971, in _add_meta_graph_for_mode
mode=mode)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 879, in _add_meta_graph_for_mode
config=self.config)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1992, in _call_model_fn
features, labels, mode, config)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 1107, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 2203, in _model_fn
features, labels, is_export_mode=is_export_mode)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1131, in call_without_tpu
return self._call_model_fn(features, labels, is_export_mode=is_export_mode)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1337, in _call_model_fn
estimator_spec = self._model_fn(features=features, **kwargs)
File "/home/cezary/models/official/mnist/mnist_tpu.py", line 95, in model_fn
cross_entropy = tf.nn.sigmoid_cross_entropy_with_logits(labels=labels, logits=logits)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_impl.py", line 156, in sigmoid_cross_entropy_with_logits
labels, logits)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1777, in _ensure_xent_args
raise ValueError("Both labels and logits must be provided.")
ValueError: Both labels and logits must be provided.
mnist命名没关系，我只是使用了代码的结构，但没有重命名。
谢谢你的帮助！