How to output the value in a dataset several times? (dataset is created by Dataset API of TensorFlow)
import tensorflow as tf
dataset = tf.contrib.data.Dataset.range(100)
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()
sess = tf.Session()
epoch = 10
for i in range(epoch):
for j in range(100):
value = sess.run(next_element)
assert j == value
print(j)
Error message:
tensorflow.python.framework.errors_impl.OutOfRangeError: End of sequence
[[Node: IteratorGetNext = IteratorGetNext[output_shapes=[[]], output_types=[DT_INT64], _device="/job:localhost/replica:0/task:0/cpu:0"](OneShotIterator)]]
How to make this work?
First of all I advice you to read Data Set Guide. There is described all the details of DataSet API.
Your question is about iterating over the data several times. Here are two solutions for that:
import tensorflow as tf
epoch = 10
dataset = tf.data.Dataset.range(100)
dataset = dataset.repeat(epoch)
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()
sess = tf.Session()
num_batch = 0
j = 0
while True:
try:
value = sess.run(next_element)
assert j == value
j += 1
num_batch += 1
if j > 99: # new epoch
j = 0
except tf.errors.OutOfRangeError:
break
print ("Num Batch: ", num_batch)
import tensorflow as tf
epoch = 10
dataset = tf.data.Dataset.range(100)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
sess = tf.Session()
num_batch = 0
for e in range(epoch):
print ("Epoch: ", e)
j = 0
sess.run(iterator.initializer)
while True:
try:
value = sess.run(next_element)
assert j == value
j += 1
num_batch += 1
except tf.errors.OutOfRangeError:
break
print ("Num Batch: ", num_batch)