TFrecords 寫入 讀取操作

#寫入操作
import tensorflow as tf
import numpy as np


writer =tf.python_io.TFRecordWriter("trainArray.tfrecords")
for _ in range(10):
    randomArray=np.random.random((1,3))
    array_raw=randomArray.tobytes()
    example=tf.train.Example(features=tf.train.Features(feature={"label":tf.train.Feature(int64_list=tf.train.Int64List(value=[1])),"img_raw":tf.train.Feature(bytes_list=tf.train.BytesList(value=[array_raw]))}))
    writer.write(example.SerializeToString())
writer.close()  

print("ok")

#讀出操作
import tensorflow as tf
import numpy as np




filename_queue=tf.train.string_input_producer(["trainArray.tfrecords"],num_epochs=None)
reader=tf.TFRecordReader()
_,serialized_example=reader.read(filename_queue)


feature=tf.parse_single_example(serialized_example,features={"label":tf.FixedLenFeature([],tf.int64)})


print(feature)


label_batch=tf.train.shuffle_batch([feature['label']],batch_size=300,capacity=200,min_after_dequeue=100,num_threads=2)
init=tf.global_variables_initializer()


sess=tf.Session()
sess.run(init)    
tf.train.start_queue_runners(sess=sess)
label=sess.run(label_batch)
label