我正在根据Keras模型创建Tensorflow估算器。当前，创建估计器，训练模型，并评估模型而不会出现问题。但是，在上一次评估中，由于我使用了FinalExporter API，因此导出了模型，并且出现尺寸不匹配错误：
INFO:tensorflow:Performing the final export in the end of training.
INFO:tensorflow:Calling model_fn.
Traceback (most recent call last):
File "/home/austinguo/.../lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1659, in _create_c_op
c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape must be rank 4 but is rank 3 for 'model/block5_conv1/Conv2D' (op: 'Conv2D') with input shapes: [14,14,512], [3,3,512,512].
当导出前在Keras模型上调用clone_model时，似乎会出现此问题（下面的回溯显示了这一点）。但是，尺寸不匹配错误似乎暗示我的输入管道有问题，这对我来说没有意义，因为如果输入函数的格式为，我不知道我的模型甚至如何可以毫无问题地训练和评估。错误或我的输入管道在其他地方断开。
完整的追溯如下：
Traceback (most recent call last):
File "/usr/lib/python3.5/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/austinguo/tf-keras_siamese/template/trainer/task.py", line 277, in <module>
main()
File "/home/austinguo/tf-keras_siamese/template/trainer/task.py", line 262, in main
experiment.run(estimator, args)
File "/home/austinguo/tf-keras_siamese/template/trainer/experiment.py", line 102, in run
tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 471, in train_and_evaluate
return executor.run()
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 611, in run
return self.run_local()
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 712, in run_local
saving_listeners=saving_listeners)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 358, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1124, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1158, in _train_model_default
saving_listeners)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1408, in _train_with_estimator_spec
any_step_done = True
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 788, in __exit__
self._close_internal(exception_type)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 821, in _close_internal
h.end(self._coordinated_creator.tf_sess)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/training/basic_session_run_hooks.py", line 588, in end
self._save(session, last_step)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/training/basic_session_run_hooks.py", line 607, in _save
if l.after_save(session, step):
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 517, in after_save
self._evaluate(global_step_value) # updates self.eval_result
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 537, in _evaluate
self._evaluator.evaluate_and_export())
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 925, in evaluate_and_export
is_the_final_export)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/training.py", line 958, in _export_eval_result
is_the_final_export=is_the_final_export))
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/exporter.py", line 419, in export
is_the_final_export)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/exporter.py", line 126, in export
strip_default_attrs=self._strip_default_attrs)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1645, in export_savedmodel
experimental_mode=model_fn_lib.ModeKeys.PREDICT)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 723, in export_saved_model
checkpoint_path=checkpoint_path)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 827, in experimental_export_all_saved_models
save_variables, mode=model_fn_lib.ModeKeys.PREDICT)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 897, in _add_meta_graph_for_mode
config=self.config)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1112, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/keras.py", line 278, in model_fn
labels)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow_estimator/python/estimator/keras.py", line 201, in _clone_and_build_model
optimizer_iterations=global_step)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/models.py", line 466, in clone_and_build_model
clone = clone_model(model, input_tensors=input_tensors)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/models.py", line 271, in clone_model
return _clone_functional_model(model, input_tensors=input_tensors)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/models.py", line 161, in _clone_functional_model
**kwargs))
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 554, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/engine/network.py", line 815, in call
mask=masks)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/engine/network.py", line 1002, in _run_internal_graph
output_tensors = layer.call(computed_tensor, **kwargs)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/keras/layers/convolutional.py", line 194, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/ops/nn_ops.py", line 966, in __call__
return self.conv_op(inp, filter)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/ops/nn_ops.py", line 591, in __call__
return self.call(inp, filter)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/ops/nn_ops.py", line 208, in __call__
name=self.name)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 1026, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
op_def=op_def)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1823, in __init__
control_input_ops)
File "/home/austinguo/census/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1662, in _create_c_op
raise ValueError(str(e))
ValueError: Shape must be rank 4 but is rank 3 for 'model/block5_conv1/Conv2D' (op: 'Conv2D') with input shapes: [14,14,512], [3,3,512,512].
任何帮助将不胜感激。谢谢！
答案 0 :(得分：1)
解决了该问题。
尺寸不匹配的原因是我使用Tensorflow的实验性make_batched_features_dataset（）数据集API。这将创建基于指定的批处理大小已批处理的数据集。但是，要使此工作正常进行，模型的输入张量需要在指定批次的开始处具有一个额外的-1尺寸，即（-1，...），其中...是其他形状尺寸。
否则，尽管在make_batched_features_dataset（）已对数据集进行批处理后不小心再次对数据集进行了批处理，但是ServingInputReceiver所提供的张量不是正确的形状。