import os
import numpy as np
import tempfile
import tensorflow as tf# example_path = os.path.join(tempfile.gettempdir(),"example.tfrecords")example_path='./temp.tfrecords'
np.random.seed(0)# Write the records to a file.
with tf.io.TFRecordWriter(example_path) as file_writer:for_ in range(4):#產(chǎn)生隨機(jī)數(shù)x, y = np.random.random(), np.random.random()print(x,y,'--->')x1=tf.train.Feature(float_list=tf.train.FloatList(value=[x]))y1=tf.train.Feature(float_list=tf.train.FloatList(value=[y]))print('x1=',x1)print('y1=',y1)feature0={"x": x1,"y":y1 ,}print('feature0=',feature0)features0=tf.train.Features(feature=feature0)print('features=',feature0)record_bytes = tf.train.Example(features=features0).SerializeToString()file_writer.write(record_bytes)# Read the data back out.
def decode_fn(record_bytes):return tf.io.parse_single_example(# Datarecord_bytes,# Schema{"x": tf.io.FixedLenFeature([], dtype=tf.float32),"y": tf.io.FixedLenFeature([], dtype=tf.float32)})for batch in tf.data.TFRecordDataset([example_path]).map(decode_fn):print("x = {x:.4f}, y = {y:.4f}".format(**batch))
