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試圖在這裏通過張量流tutorial;我用〜100個圖像構建一個tf記錄文件,現在當我嘗試以下操作時,內核會掛起;這是爲什麼發生?課題組記錄文件不是很大隻有30MB +左右,它不應該採取長期在閱讀他們:讀取TF記錄文件需要很長時間
import tensorflow as tf
import os
print(os.path.exists("../carmakesorter/train-00000-of-00001"))
filenameQ = tf.train.string_input_producer(["../carmakesorter/train-00000-of-00001"],num_epochs=None)
# object to read records
recordReader = tf.TFRecordReader()
# read the full set of features for a single example
key, fullExample = recordReader.read(filenameQ)
# parse the full example into its' component features.
features = tf.parse_single_example(
fullExample,
features={
'image/height': tf.FixedLenFeature([], tf.int64),
'image/width': tf.FixedLenFeature([], tf.int64),
'image/colorspace': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
'image/channels': tf.FixedLenFeature([], tf.int64),
'image/class/label': tf.FixedLenFeature([],tf.int64),
'image/class/text': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
'image/format': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
'image/filename': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
'image/encoded': tf.FixedLenFeature([], dtype=tf.string, default_value='')
})
label = features['image/class/label']
with tf.Session() as sess:
print('start ...')
print(sess.run(label)) # I want to check the label here
print('end ...')
它打印:
True
start ...
我的筆記本內核掛起10分鐘,已經和我看不到會有結局。有人能指出我做錯了什麼嗎?