export_saved_model在 TPUEstimator 上使用会引发 TypeError：无法使用 Tensorflow 1.12.0 将类型对象转换为张量。我是否使用不正确，或者如果它是一个错误，是否有一些解决方法？
我想使用 TPUEstimator 在 TPU 上训练一个模型，然后在 CPU 上本地使用训练后的模型。我不能直接使用训练期间保存的图表，但我需要使用export_saved_model（Github issue）。
export_saved_model在 TPUEstimator 上可以与 Tensorflow 1.13.0rc0 一起正常工作，但是在当前的 Tensorflow 1.12.0 上会失败（另一个 Github 问题）。但是，目前 Google Cloud 上不提供带有 Tensorflow 1.13 的 TPU，并且带有 Tensorflow 1.12 的 TPU 不兼容，因此无法将 Tensorflow 升级到 1.13。
相关代码为：
def serving_input_receiver_fn():
feature = tf.placeholder(tf.float32, shape=[None, None, None, 2])
return tf.estimator.export.TensorServingInputReceiver(feature, feature)
estimator.export_saved_model(FLAGS.export_dir, serving_input_receiver_fn)
预期结果。 模型应正确导出。这发生在 Tensorflow 1.13.0rc0 或 TPUEstimator 被 Estimator 取代。前者可以使用这个 colab 复制）。
实际结果。 导出失败并出现 TypeError: Failed to convert object of type 和下面包含的回溯。这可以用这个 colab 复制。
...
WARNING:tensorflow:From /Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py:1044: calling SavedModelBuilder.add_meta_graph_and_variables (from tensorflow.python.saved_model.builder_impl) with legacy_init_op is deprecated and will be removed in a future version.
Instructions for updating:
Pass your op to the equivalent parameter main_op instead.
INFO:tensorflow:Assets added to graph.
INFO:tensorflow:No assets to write.
WARNING:tensorflow:rewrite_for_inference (from tensorflow.contrib.tpu.python.tpu.tpu) is experimental and may change or be removed at any time, and without warning.
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Running infer on CPU
ERROR:tensorflow:Operation of type Placeholder (policy_labels) is not supported on the TPU. Execution will fail if this op is used in the graph.
ERROR:tensorflow:Operation of type Placeholder (sat_labels) is not supported on the TPU. Execution will fail if this op is used in the graph.
INFO:tensorflow:Done calling model_fn.
Traceback (most recent call last):
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 527, in make_tensor_proto
str_values = [compat.as_bytes(x) for x in proto_values]
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 527, in <listcomp>
str_values = [compat.as_bytes(x) for x in proto_values]
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/util/compat.py", line 61, in as_bytes
(bytes_or_text,))
TypeError: Expected binary or unicode string, got dict_values([<tf.Tensor 'sat_prob:0' shape=(?,) dtype=float32>, <tf.Tensor 'policy_prob:0' shape=(?, ?, 2) dtype=float32>])
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "neurosat_tpu.py", line 253, in <module>
tf.app.run()
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "neurosat_tpu.py", line 248, in main
estimator.export_saved_model(FLAGS.export_dir, serving_input_receiver_fn)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 734, in export_saved_model
strip_default_attrs=True)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 663, in export_savedmodel
mode=model_fn_lib.ModeKeys.PREDICT)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 789, in _export_saved_model_for_mode
strip_default_attrs=strip_default_attrs)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 907, in _export_all_saved_models
mode=model_fn_lib.ModeKeys.PREDICT)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 2188, in _add_meta_graph_for_mode
check_variables=False))
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 984, in _add_meta_graph_for_mode
config=self.config)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 2192, in _call_model_fn
return self._call_model_fn_for_inference(features, labels, mode, config)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 2253, in _call_model_fn_for_inference
new_tensors.append(array_ops.identity(t))
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 81, in identity
return gen_array_ops.identity(input, name=name)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3454, in identity
"Identity", input=input, name=name)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 513, in _apply_op_helper
raise err
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1146, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 229, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 208, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/Users/michal/.virtualenvs/deepsat/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 531, in make_tensor_proto
"supported type." % (type(values), values))
TypeError: Failed to convert object of type <class 'dict_values'> to Tensor. Contents: dict_values([<tf.Tensor 'sat_prob:0' shape=(?,) dtype=float32>, <tf.Tensor 'policy_prob:0' shape=(?, ?, 2) dtype=float32>]). Consider casting elements to a supported type.