import tensorflow.contrib.slim as slim ModuleNotFoundError: No module named 'tensorflow.contrib

.slim'

This error occurs when the TensorFlow version being used does not have the "contrib" module. This module contains a lot of useful functions and tools that can be used for deep learning tasks. To resolve this error, you can try installing an older version of TensorFlow that has the "contrib" module or use another deep learning framework that has similar functionality. Alternatively, you can try updating your TensorFlow version to the latest version that has the "contrib" module.

相关问题

import tensorflow.contrib.slim as slim ModuleNotFoundError: No module named 'tensorflow.contrib'

引用中的报错信息显示，在代码中使用了tensorflow.contrib.slim模块，但是系统找不到这个模块，导致报错。而引用提供了一个解决方案，即将import tensorflow.contrib.slim as slim 改为 import tf_slim as slim，这样可以成功解决该报错。此外，引用还提供了另外一个解决方案，即降低tensorflow版本。你可以使用命令pip uninstall tensorflow卸载当前版本，然后使用pip install tensorflow==1.14.0安装tensorflow 1.14.0版本来解决该问题。这两种解决方案可以根据具体情况选择其中一种来解决导入模块报错的问题。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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将 tensorflow.contrib.slim 导入为 slim ModuleNotFoundError: No module named 'tensorflow.contrib' 修改代码使用于TensorFlow2.x

在 TensorFlow 2.x 中，`tensorflow.contrib` 已经被移除了。为了使用Slim，可以按照以下步骤进行：

1. 安装 TensorFlow 2.x 和 TensorFlow Addons（用于一些额外的功能）:

!pip install tensorflow==2.5.0
!pip install tensorflow-addons

2. 导入 `tensorflow_addons` 和 `tensorflow.keras`:

import tensorflow_addons as tfa
import tensorflow.keras as keras

3. 通过 `keras` 导入 `slim`:

from tensorflow.keras import layers
from tensorflow.keras import backend as K
from tensorflow.keras.models import Model

from tensorflow.keras.applications import imagenet_utils
from tensorflow.keras.applications import ResNet50

from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.preprocessing.image import load_img

from tensorflow.keras.applications.mobilenet_v2 import MobileNetV2
from tensorflow.keras.applications.mobilenet_v2 import preprocess_input as mobilenet_v2_preprocess_input

from tensorflow.keras.applications.inception_v3 import InceptionV3
from tensorflow.keras.applications.inception_v3 import preprocess_input as inception_v3_preprocess_input

from tensorflow.keras.applications.vgg16 import VGG16
from tensorflow.keras.applications.vgg16 import preprocess_input as vgg16_preprocess_input

from tensorflow.keras.applications.resnet_v2 import ResNet50V2
from tensorflow.keras.applications.resnet_v2 import preprocess_input as resnet_v2_preprocess_input

from tensorflow.keras.applications.efficientnet import EfficientNetB0
from tensorflow.keras.applications.efficientnet import preprocess_input as efficientnet_preprocess_input

from tensorflow.keras.applications.nasnet import NASNetMobile
from tensorflow.keras.applications.nasnet import preprocess_input as nasnet_preprocess_input

from tensorflow.keras.applications.xception import Xception
from tensorflow.keras.applications.xception import preprocess_input as xception_preprocess_input

import tensorflow_hub as hub

from typing import List, Tuple
import numpy as np
import cv2

这样就可以使用 Slim 的一些功能了。需要注意的是，Slim 在 TensorFlow 2.x 中已经不是官方支持的模块，因此在使用时需要自行承担风险。