FPRECOND tensorflow runtime_error ai_generated true

FailedPreconditionError: GetNext() failed because the iterator has not been initialized

ID: tensorflow/iterator-get-next-failed-precondition

Also available as: JSON · Markdown · 中文

90%Fix Rate

85%Confidence

1Evidence

2023-05-10First Seen

Version Compatibility

Version	Status	Introduced	Deprecated	Notes
tensorflow 2.10	active	—	—	—
tensorflow 2.11	active	—	—	—
tensorflow 2.12	active	—	—	—

Root Cause

A tf.data iterator was used without being initialized, typically in TF1 style code or when using tf.compat.v1.data.make_one_shot_iterator incorrectly.

generic

中文

tf.data 迭代器在使用前未初始化，常见于 TF1 风格代码或错误使用 tf.compat.v1.data.make_one_shot_iterator。

Official Documentation

https://www.tensorflow.org/guide/data#using_the_iterator_api

Workarounds

90% success Initialize the iterator explicitly before fetching: iterator = dataset.make_initializable_iterator(); sess.run(iterator.initializer); then sess.run(get_next).
```
Initialize the iterator explicitly before fetching: iterator = dataset.make_initializable_iterator(); sess.run(iterator.initializer); then sess.run(get_next).
```
95% success Switch to TF2-style eager iteration: for batch in dataset: ... instead of using iterators.
```
Switch to TF2-style eager iteration: for batch in dataset: ... instead of using iterators.
```

中文步骤

Initialize the iterator explicitly before fetching: iterator = dataset.make_initializable_iterator(); sess.run(iterator.initializer); then sess.run(get_next).

Switch to TF2-style eager iteration: for batch in dataset: ... instead of using iterators.

Dead Ends

Common approaches that don't work:

95% fail
The iterator still lacks initialization; only a fresh session restart is attempted.
85% fail
The initialization must happen before any get_next call, not after.