Shape must be rank 0 but is rank 1, parse_single_sequence_example - tensorflow

Question

For the past few days I have been having an issue with serializing data to tfrecord format and then subsequently deserializing it using parse_single_sequence example. I am attempting to retrieve data for use with a fairly standard RNN model, however this is my first attempt at using the tfrecords format and the associated pipeline that goes with it.
Here is a toy example to reproduce the issue I am having:
import tensorflow as tf
import tempfile
from IPython import embed
sequences = [[1, 2, 3], [4, 5, 1], [1, 2]]
label_sequences = [[0, 1, 0], [1, 0, 0], [1, 1]]
def make_example(sequence, labels):
ex = tf.train.SequenceExample()
sequence_length = len(sequence)
ex.context.feature["length"].int64_list.value.append(sequence_length)
fl_tokens = ex.feature_lists.feature_list["tokens"]
fl_labels = ex.feature_lists.feature_list["labels"]
for token, label in zip(sequence, labels):
fl_tokens.feature.add().int64_list.value.append(token)
fl_labels.feature.add().int64_list.value.append(label)
return ex
writer = tf.python_io.TFRecordWriter('./test.tfrecords')
for sequence, label_sequence in zip(sequences, label_sequences):
ex = make_example(sequence, label_sequence)
writer.write(ex.SerializeToString())
writer.close()
tf.reset_default_graph()
file_name_queue = tf.train.string_input_producer(['./test.tfrecords'], num_epochs=None)
reader = tf.TFRecordReader()
context_features = {
"length": tf.FixedLenFeature([], dtype=tf.int64)
}
sequence_features = {
"tokens": tf.FixedLenSequenceFeature([], dtype=tf.int64),
"labels": tf.FixedLenSequenceFeature([], dtype=tf.int64)
}
ex = reader.read(file_name_queue)
# Parse the example (returns a dictionary of tensors)
context_parsed, sequence_parsed = tf.parse_single_sequence_example(
serialized=ex,
context_features=context_features,
sequence_features=sequence_features
)
context = tf.contrib.learn.run_n(context_parsed, n=1, feed_dict=None)
print(context[0])
sequence = tf.contrib.learn.run_n(sequence_parsed, n=1, feed_dict=None)
print(sequence[0])
The associated stack trace is:
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/common_shapes.py", line 594, in call_cpp_shape_fn
status)
File "/usr/lib/python3.5/contextlib.py", line 66, in exit
next(self.gen)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/errors.py", line 463, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors.InvalidArgumentError: Shape must be rank 0 but is rank 1
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "my_test.py", line 51, in
sequence_features=sequence_features
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/parsing_ops.py", line 640, in parse_single_sequence_example
feature_list_dense_defaults, example_name, name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/parsing_ops.py", line 837, in _parse_single_sequence_example_raw
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_parsing_ops.py", line 285, in _parse_single_sequence_example
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 749, in apply_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2382, in create_op
set_shapes_for_outputs(ret)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1783, in set_shapes_for_outputs
shapes = shape_func(op)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/common_shapes.py", line 596, in call_cpp_shape_fn
raise ValueError(err.message)
ValueError: Shape must be rank 0 but is rank 1
I posted this as a potential issue over on github though it seems I may just be using it incorrectly: Tensorflow Github Issue
So with the background information out of the way, I'm just wondering if I am in fact making an error here? Any help in the right direction would be greatly appreciated, its been a few days and my poking around hasn't panned out. Thanks all!

Answer 1

Got it and it was a bad assumption on my part. The tf.TFRecordReader.read(queue, name=None) returns a tuple when I assumed it would have returned just the value not (key, value) which I was directly passing into the example parser.