Tensorflow 2.16.0+在PyCharm中找不到keras的报错解决

在PyCharm(2024.2版本)中,直接使用from tensorflow import keras会提示"Cannot find reference 'keras' in 'init .py' ",找不到keras,如下图所示。

查阅相关资料,可以发现在tf2.16之后,默认的keras后端升级为了3.0,且直接引用即可。

参考链接:PyCharm cannot parse any content under tensorflow.keras 2.16.2 #73110

以及:Introducing Keras 3.0

TF 2.15: Keras2.0

python 复制代码
import tensorflow as tf
from tensorflow import keras

TF 2.16: Keras 3.0

python 复制代码
import tensorflow as tf
import keras

reddit上也有人讨论:

Because in the old days Keras was entirely separate to Tensorflow. It had a backend for Theano and maybe some other stuff. Then Francois and the TF team at Google decided to bring Keras into TF as their main high level API, trying to address the fragmentation that had been created in TF land. Since TF usage is dwindling in research, and possibly showing signs of similar in industry, Keras is now multi-backend again, supporting TensorFlow, PyTorch, and JAX.

  1. Very old code will import keras directly, and be referring to Keras 1. This code will usually use > Theano or TensorFlow 1.x as well.
  2. More recent code will import tensorflow.keras and be referring to Keras 2. This is the majority of the code you'll find.
  3. Very recent code (i.e. this year I think) will import keras directly again, or maybe keras_core, and be referring to Keras 3, the latest version.

也就是说,在最新版(2.16.0+)的Tensorflow中,只需要直接引用import keras即可正常使用keras3.0。经测试,使用keras.modelskeras.layers均可正常使用,也会有代码补全。

相关推荐
淘矿人14 小时前
[特殊字符] 别再手动写提示词了!Claude Skills 10分钟入门,效率暴涨200%,Token狂省78%
人工智能·vscode·python·pycharm·github·文心一言·ai编程
小鸡吃米…2 天前
TensorFlow - 数学基础
人工智能·python·tensorflow
golang学习记2 天前
PyCharm 2025.3.2 正式支持 Google Colab:本地 IDE + 云端算力,无缝开发!
ide·python·pycharm
勾股导航2 天前
TensorFlow GPU版本
人工智能·python·tensorflow
Tech Synapse2 天前
Python详细安装教程——Python及PyCharm超详细安装教程:新手小白也能轻松搞定!(最新版)
python·pycharm·详细安装教程
小鸡吃米…3 天前
人工智能的理解
python·tensorflow
小鸡吃米…3 天前
TensorFlow 安装教程
python·tensorflow
wVelpro4 天前
如何在Pycharm 2025.3 版本实现虚拟环境“Make available to all projects”
linux·ide·pycharm
却道天凉_好个秋4 天前
Tensorflow数据增强(三):高级裁剪
人工智能·深度学习·tensorflow
Coder_Boy_4 天前
TensorFlow小白科普
人工智能·深度学习·tensorflow·neo4j