Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
785 views
in Technique[技术] by (71.8m points)

python - Tensorflow TFRecord: Can't parse serialized example

I am trying to follow this guide in order to serialize my input data into the TFRecord format but I keep hitting this error when trying to read it:

InvalidArgumentError: Key: my_key. Can't parse serialized Example.

I am not sure where I'm going wrong. Here is a minimal reproduction of the issue I cannot get past.

Serialise some sample data:

with tf.python_io.TFRecordWriter('train.tfrecords') as writer:
  for idx in range(10):
        example = tf.train.Example(
            features=tf.train.Features(
                feature={
                    'label': tf.train.Feature(int64_list=tf.train.Int64List(value=[1,2,3])),
                    'test': tf.train.Feature(float_list=tf.train.FloatList(value=[0.1,0.2,0.3])) 
                }
            )
        )

        writer.write(example.SerializeToString())
  writer.close()

Parsing function & deserialise:

def parse(tfrecord):
  features = {
      'label': tf.FixedLenFeature([], tf.int64, default_value=0),
      'test': tf.FixedLenFeature([], tf.float32, default_value=0.0),
  }
  return tf.parse_single_example(tfrecord, features)

dataset = tf.data.TFRecordDataset('train.tfrecords').map(parse)
getnext = dataset.make_one_shot_iterator().get_next()

When trying to run this:

with tf.Session() as sess:
  v = sess.run(getnext)
  print (v)

I trigger the above error message.

Is it possible to get past this error and deserialize my data?

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

tf.FixedLenFeature() is used for reading the fixed size arrays of data. And the shape of the data should be defined beforehand. Updating the parse function to

def parse(tfrecord):
   return tf.parse_single_example(tfrecord, features={
       'label': tf.FixedLenFeature([3], tf.int64, default_value=[0,0,0]),
       'test': tf.FixedLenFeature([3], tf.float32, default_value=[0.0, 0.0, 0.0]),
   })

Should do the job.


与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...