将数据集转化为tfrecord并读取tfrecord

    **//将数据集转化为tfrecord**
        import tensorflow as tf
        from tensorflow.examples.tutorials.mnist import input_data
        import numpy as np
        
        def _int64_feature(value):
            return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]));
        
        def _bytes_feature(value):
            return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]));
        
        mnist=input_data.read_data_sets("../mnist",dtype=tf.uint8,one_hot=True);
        images=mnist.train.images;
        labels=mnist.train.labels;
        pixels=images.shape[1];
        num_examples=mnist.train.num_examples;
        
        filename="log/output.tfrecords";
        writer=tf.python_io.TFRecordWriter(filename);
        for index in range(num_examples):
            image_raw=images[index].tostring();
            example=tf.train.Example(features=tf.train.Features(feature={
                        'pixels':_int64_feature(pixels),
                        'labels':_int64_feature(np.argmax(labels[index])),
                        'image_raw':_bytes_feature(image_raw)
                    }));
            writer.write(example.SerializeToString());
        
        writer.close();

**//读取tfrecord**
import tensorflow as tf
reader=tf.TFRecordReader();
filename_queue=tf.train.string_input_producer(["log/output.tfrecords"]);
_,serialized_example=reader.read(filename_queue);
features=tf.parse_single_example(
	serialized_example,
	features={
        'image_raw':tf.FixedLenFeature([],tf.string),
        'pixels':tf.FixedLenFeature([],tf.int64),
        'labels':tf.FixedLenFeature([],tf.int64),
    });

images=tf.decode_raw(features['image_raw'],tf.uint8);
labels=tf.cast(features['labels'],tf.int32);
pixels=tf.cast(features['pixels'],tf.int32);

with tf.Session() as sess:
    # coord=tf.train.Coordinator();
    # threads=tf.train.start_queue_runners(sess=sess,coord=coord);
    for i in range(10):
        image,label,pixel=sess.run([images,labels,pixels]);
        print(image);